imf-mcp-server
Server Details
Query IMF SDMX 3.0 macroeconomic dataflows — WEO, BOP, CPI, exchange rates, 190 countries.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- cyanheads/imf-mcp-server
- GitHub Stars
- 1
- Server Listing
- imf-mcp-server
Available Tools
5 toolsimf_dataframe_describeImf Dataframe DescribeARead-onlyIdempotentInspect
List DataCanvas tables and columns staged by a prior imf_query_dataset call. Returns each table's name, row count, and column schema (name + DuckDB type). Required before imf_dataframe_query to discover the table and column names for SQL.
| Name | Required | Description | Default |
|---|---|---|---|
| canvas_id | Yes | Canvas ID returned by imf_query_dataset whenever staged=true, from automatic spillover or output_mode="canvas". |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | Present when the call failed. Absent on success. |
| tables | No | All tables registered on this canvas. |
| canvas_id | No | Canvas session ID that was introspected. |
| table_count | No | Total number of tables on the canvas. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds meaningful behavioral detail: it returns row counts and column schemas for tables staged by a previous call, and it exposes DuckDB types. There is no contradiction with the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two dense sentences with no filler. The action and scope are front-loaded, and the 'Required before imf_dataframe_query' clause gives essential workflow context without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter, read-only, idempotent introspection tool with a rich input schema and an output schema present, the description fully equips an agent to select and invoke it correctly. Nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage of the single canvas_id parameter, including its origin conditions (staged=true, automatic spillover, output_mode="canvas"). The description reinforces that context but does not add new parameter-level meaning, so the high-coverage baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('List') and resource ('DataCanvas tables and columns staged by a prior imf_query_dataset call'), then specifies the return content: table name, row count, and column schema with DuckDB types. It also distinguishes itself from imf_dataframe_query by framing this as the discovery step needed before querying.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly defines when to use it: after imf_query_dataset and before imf_dataframe_query, since it is required to discover table/column names for SQL. It does not explicitly list exclusions for other sibling tools like imf_list_databases, but the sequencing and prerequisite context are strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
imf_dataframe_queryImf Dataframe QueryARead-onlyIdempotentInspect
Run a read-only SQL SELECT against a DataCanvas table staged by imf_query_dataset. Supports multi-country comparisons, time-series aggregation, and cross-indicator joins. Requires imf_dataframe_describe first to discover table and column names. One SELECT statement per call; a leading WITH … SELECT (CTE) is accepted. DML and DDL are rejected.
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes | Read-only SQL SELECT statement — exactly one statement, starting with SELECT or with a WITH … SELECT common table expression. Reference tables by the names returned by imf_dataframe_describe. Example: SELECT time_period, value FROM spilled_abc123 WHERE time_period >= '2010' ORDER BY time_period. | |
| canvas_id | Yes | Canvas ID returned by imf_query_dataset whenever staged=true. Call imf_dataframe_describe with it before writing SQL. |
Output Schema
| Name | Required | Description |
|---|---|---|
| rows | No | Largest result-row prefix whose complete structured and formatted response fits the 100,000-character response budget, after the canvas row limit (default 10,000) is applied. |
| error | No | Present when the call failed. Absent on success. |
| row_count | No | Number of materialized rows returned in rows. Always equals rows.length and never claims a pre-cap total. |
| truncated | No | True when DataCanvas capped the query at its row limit or the server omitted materialized rows to fit the response-size budget. Page the remainder with a stable ORDER BY plus LIMIT/OFFSET, or narrow the query with WHERE or aggregation. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and idempotent behavior. The description adds valuable constraints beyond annotations: one statement per call, CTE acceptance, rejection of DML/DDL, and the prerequisite to call imf_dataframe_describe first. There is no contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each carrying distinct information: operation scope, supported analysis types, prerequisite, and statement constraints. The most important behavioral rule (read-only SELECT) is front-loaded, with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the prerequisite workflow, call constraints, accepted SQL shapes, and rejected statement types. With a provided output schema and read-only/idempotent annotations, an agent has enough context to invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already provides detailed parameter semantics for both sql and canvas_id. The description reinforces the prerequisite relationship but does not add much parameter meaning beyond what the schema already supplies, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Run'), resource ('a DataCanvas table staged by imf_query_dataset'), and operation type ('read-only SQL SELECT'). It distinguishes itself from siblings by positioning itself as the query layer over staged tables, while imf_dataframe_describe handles discovery.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage context: it must follow imf_dataframe_describe, applies to staged tables, and accepts one SELECT or WITH...SELECT. It doesn't explicitly contrast with sibling query tools like imf_get_database or imf_query_dataset, but the staged-table prerequisite makes the intended workflow clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
imf_get_databaseImf Get DatabaseARead-onlyIdempotentInspect
Fetch a dataflow's dimension list with a codelist preview for each dimension. Resolves human-readable terms to SDMX codes (e.g. "United States" → USA, "Constant prices" → NGDP_RPCH). Required before imf_query_dataset — SDMX keys are opaque without codelist lookups. Each codelist is capped at the first 50 entries by default, including previews filtered by codelist_filter. Set dimension_id to retrieve one codelist with bounded limit/offset paging after the optional substring filter. Set available_only=true to page codes the dataflow actually publishes, with series and time coverage metadata; availability filtering happens before codelist_filter and paging. The imf://database/{dataflow_id} resource provides the same bounded discovery summary. Country codes are ISO 3-letter (USA, GBR, DEU), not ISO 2-letter (US, GB, DE). The key_format field shows the exact dimension order required by imf_query_dataset. Note: codelists enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series in this dataflow.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Entries to return from the selected dimension. Valid only with dimension_id; default 50, maximum 200. | |
| offset | No | Matching entries to skip in the selected dimension before this page. Valid only with dimension_id; default 0. | |
| version | No | Dataflow version, e.g. 9.0.0. Auto-detected from the dataflow list when omitted. | |
| agency_id | No | Agency ID that publishes this dataflow, e.g. IMF.RES or IMF.STA. Auto-detected from the dataflow list when omitted. | |
| dataflow_id | Yes | Dataflow identifier from imf_list_databases, e.g. WEO, BOP, CPI. Case-sensitive. | |
| dimension_id | No | Exact dimension ID from this tool, e.g. INDICATOR. Select one dimension to page beyond its preview. | |
| available_only | No | Return only codes reported by the dataflow-wide availability constraint. Default false keeps ordinary codelist discovery unchanged. | |
| codelist_filter | No | Optional case-insensitive substring to search within each dimension's codelist (code ID and name). Filtering runs before the 50-entry preview or selected-dimension page. Example: "CPI" or "Constant prices" surfaces matching WEO indicator codes. |
Output Schema
| Name | Required | Description |
|---|---|---|
| name | No | Human-readable dataflow name. |
| error | No | Present when the call failed. Absent on success. |
| notice | No | Populated when a codelist_filter matched no entries anywhere, or when a dimension has no resolvable codelist, or when offset is past the final match. |
| source | No | Attribution string required by IMF data terms: "Source: International Monetary Fund, <dataflow name>, <link>". |
| version | No | Dataflow version string, e.g. 9.0.0. |
| agency_id | No | Agency that publishes this dataflow, e.g. IMF.RES, IMF.STA. |
| truncated | No | True when any returned dimension page omits matching codes. |
| dimensions | No | All dimension previews, or the one selected dimension page. |
| key_format | No | Dimension names in dot-separated keyPosition order, e.g. COUNTRY.INDICATOR.FREQUENCY. Use this exact format when constructing the key for imf_query_dataset. |
| dataflow_id | No | Dataflow identifier, e.g. WEO, BOP, CPI. |
| description | No | This dataflow's own description in full — not the shared DSD's, and not the shortened preview imf_list_databases returns for the same id. Absent when the dataflow publishes none. |
| dsd_version | No | Version of the underlying data structure definition (DSD) that backs this dataflow. Differs from version when the dataflow references a shared DSD (e.g. IIP → DSD_BOP at 24.0.0). |
| dimension_id | No | Selected dimension ID. Absent when previews for every dimension were returned. |
| series_count | No | Total series published by the dataflow. Present when available_only is true. |
| structure_ref | No | Identifier of the underlying DSD, e.g. DSD_BOP. Several dataflows can share one DSD. |
| available_only | No | True when dimensions contain published availability coverage rather than codelists. |
| codelist_filter | No | Echo of the codelist_filter that produced this result. Absent when no filter was applied — an empty codelist then means the codelist could not be resolved, not that the filter missed. |
| time_period_end | No | Latest period with published data, or null when the constraint omits it. |
| time_period_start | No | Earliest period with published data, or null when the constraint omits it. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds substantial beyond-annotation behavior: the 50-entry codelist cap, filtering-before-paging order, availability-only mode semantics, ISO 3-letter vs 2-letter country codes, and the caveat that valid codes can still return no_data. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but every sentence earns its place: purpose, prerequisite, pagination, filtering, resource equivalence, code-format warning, and a no_data caveat. It is front-loaded with the primary action and required context, and the later sentences cover edge cases that prevent misinvocation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a complex 8-parameter tool, but the schema fully documents all parameters and an output schema exists. The description provides the missing operational context: ordering of filters, paging behavior, the prerequisite relationship to imf_query_dataset, and a key caveat about codelist coverage versus actual data. Nothing critical is left for the agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explaining operational semantics such as 'availability filtering happens before codelist_filter and paging,' giving a concrete codelist_filter example, and noting the key_format field's role. This lifts it above baseline without making it a full parameter-by-parameter walkthrough.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Fetch a dataflow's dimension list with a codelist preview for each dimension.' It gives concrete examples of SDMX code resolution ("United States" → USA) and explicitly distinguishes the tool's role from imf_query_dataset by stating it must be run first.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states the tool is required before imf_query_dataset because SDMX keys are opaque without codelist lookups. It also clarifies when to use dimension_id, available_only, and codelist_filter. It does not explicitly exclude sibling tools beyond noting the prerequisite relationship, but the use context is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
imf_list_databasesImf List DatabasesARead-onlyIdempotentInspect
List IMF SDMX dataflows available on the portal. Entry point for every query: imf_get_database and imf_query_dataset both require a dataflow id obtained here. Vintage (historical snapshot) dataflows such as WEO_2025_OCT_VINTAGE are excluded by default; set include_vintages=true to include them. Results are paged — 50 per call by default, adjustable with limit and offset — and total_count reports how many dataflows matched. Descriptions are shortened here; imf_get_database returns the full text for a single dataflow.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum dataflows to return in this call. Default 50, ceiling 200; total_count reports how many matched, so a partial page is always recognizable as one. | |
| filter | No | Optional name, ID, or description substring to filter results. Case-insensitive. Example: "exchange rate" returns ER and related dataflows. | |
| offset | No | Number of matching dataflows to skip before this page. Combine with limit to page through a broad or unfiltered catalog. | |
| include_vintages | No | Include vintage (historical snapshot) dataflows such as WEO_2025_OCT_VINTAGE. Default false — vintages are excluded to keep the discovery surface clean. |
Output Schema
| Name | Required | Description |
|---|---|---|
| cap | No | The limit that bounded this page. |
| error | No | Present when the call failed. Absent on success. |
| shown | No | Dataflows returned in this page. |
| notice | No | Populated when the filter matches nothing, or when matches remain beyond this page — explains why and names the next offset to request. |
| offset | No | Number of matching dataflows skipped before this page. |
| dataflows | No | This page of matching dataflows; pass the id to imf_get_database to resolve dimension codelists. |
| truncated | No | True when matching dataflows remain beyond this page. |
| total_count | No | Dataflows matching filter and include_vintages, before limit and offset are applied. Exceeds returned_count when more pages remain. |
| returned_count | No | Dataflows in this page — the length of dataflows. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint, openWorldHint, and idempotentHint already present, the description adds meaningful behavioral context beyond those annotations: vintages are excluded by default, results are paged at 50 per call, total_count reports matches, and descriptions are shortened in this listing. These traits are not derivable from the annotations and materially shape how an agent interprets results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a compact four-sentence paragraph, each sentence earning its place: core action, entry-point role, the vintage caveat, pagination behavior, and a pointer to an alternative for fuller descriptions. It is front-loaded with the primary purpose and contains no filler or redundant restatements.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential operational context: why this tool must be called first, default exclusions, pagination semantics, total_count availability, and where to get fuller data. Since an output schema exists, the description need not spell out the return shape, and nothing required for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers all four parameters with defaults and prose descriptions at 100% coverage, so the baseline applies. The description's paging and vintage-exclusion statements mirror schema content rather than adding new semantic information, though they do reinforce the intended use of limit, offset, and include_vintages in context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'List IMF SDMX dataflows available on the portal.' It clearly distinguishes the tool from siblings by identifying imf_get_database and imf_query_dataset as consumers of the IDs returned here, and contrasts the abbreviated descriptions with the full text available from imf_get_database.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly positions the tool as the 'Entry point for every query' and notes that both imf_get_database and imf_query_dataset require a dataflow id obtained here, telling agents when to use it. It also provides guidance on alternatives by noting that full descriptions live in imf_get_database, and sprinkles conditionals like 'set include_vintages=true' for when vintages are needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
imf_query_datasetImf Query DatasetARead-onlyIdempotentInspect
Query an IMF SDMX dataflow by dimension key over a time range. Returns observations with time_period, value, and status, plus the unit, scale, and decimals of each series — a key resolving to several series carries one entry per series in series_metadata, since unit and scale differ between them. Requires imf_get_database first to obtain the correct key_format and valid dimension codes. Country codes are ISO 3-letter (USA, GBR, DEU — not US, GB, DE). Key format: dot-separated codes in DSD keyPosition order (e.g. USA.NGDP_RPCH.A for WEO). Every position must carry a code: use + to combine codes (e.g. USA+GBR.NGDP_RPCH.A) and * to match every code at a position (e.g. *.NGDP_RPCH.A for all countries). Codelists from imf_get_database enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series. start_period and end_period must be valid period strings (YYYY, YYYY-SN, YYYY-QN, YYYY-MM, or a calendar-valid YYYY-MM-DD) with start_period no later than end_period; malformed or reversed ranges are rejected. A bound covers the whole period it names, so end_period 2023 includes 2023-M12 and 2023-Q4. Large analytical result sets (multi-country, long time range) spill to DataCanvas; call imf_dataframe_describe first to inspect staged tables and columns, then imf_dataframe_query for SQL analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Dot-separated dimension codes in DSD keyPosition order. Call imf_get_database to get key_format and valid codes first. Use + to combine codes at one position (e.g. USA+GBR.NGDP_RPCH.A). Use * to match every code at a position — *.NGDP_RPCH.A returns the indicator for all countries, and CAN.*.A every indicator for Canada. Every position needs a code or a *; an empty segment (USA..A) is rejected. Country codes are ISO 3-letter: USA not US, GBR not GB, DEU not DE. | |
| version | No | Dataflow version. Auto-detected from dataflow list when omitted. | |
| agency_id | No | Agency ID, e.g. IMF.RES or IMF.STA. Auto-detected from dataflow list when omitted. | |
| canvas_id | No | Existing canvas ID to accumulate results into across multiple queries. This selects the destination only; it does not force staging. Use output_mode="canvas" to stage an under-budget result. | |
| end_period | No | End of time range (inclusive). Same formats as start_period, and must not be earlier than it. The bound covers the whole period it names, so end_period 2023 admits 2023-M12 and 2023-Q4. Observations after this period are excluded from the result. | |
| dataflow_id | Yes | Dataflow identifier from imf_list_databases, e.g. WEO, BOP, CPI. | |
| output_mode | No | Result placement. auto returns an under-budget result inline and spills only when needed. canvas explicitly stages the full result, using canvas_id when supplied or allocating a fresh canvas. | auto |
| start_period | No | Start of time range (inclusive). Accepts any of YYYY (annual), YYYY-SN (semi-annual, e.g. 2023-S1), YYYY-QN (quarterly, e.g. 2023-Q1), YYYY-MM (monthly), or a calendar-valid YYYY-MM-DD (daily), whatever the dataflow's frequency. The bound covers the whole period it names, so start_period 2023 admits 2023-M01 and 2023-Q1. Observations before this period are excluded from the result. |
Output Schema
| Name | Required | Description |
|---|---|---|
| key | No | Dimension key used in the query, e.g. USA.NGDP_RPCH.A. |
| error | No | Present when the call failed. Absent on success. |
| notice | No | Populated when a period bound was set but some observations carry a time_period label the range filter does not recognize. Composes with staged retrieval_guidance when both apply. |
| source | No | Attribution string required by IMF data terms: "Source: International Monetary Fund, <dataflow name>, <link>". |
| staged | No | True when the complete observation set is stored on DataCanvas. canvas_id and table_name are present whenever true. |
| canvas_id | No | DataCanvas session ID — present when staged=true. Pass first to imf_dataframe_describe, then to imf_dataframe_query. |
| truncated | No | True only when observations is an incomplete preview of observation_count. A result can be staged=true and truncated=false when every observation also fits inline. |
| end_period | No | Latest period covered; absent when the full available range was used. |
| table_name | No | DuckDB table name on the canvas — present when staged=true; reference in SQL via FROM <table_name>. |
| dataflow_id | No | Dataflow identifier that was queried, e.g. WEO. |
| observations | No | Inline observation preview. For staged results this may contain the full set or a budget-limited prefix; observation_count remains the full count. |
| start_period | No | Earliest period covered; absent when the full available range was used. |
| series_metadata | No | Per-series attributes, one entry per distinct series_key in the result. Present only when the query resolved to more than one series; a single-series query carries its values in series_attributes instead. Unit and scale differ across series in one query — WEO NGDPD is USD at scale 9 while NGDP_RPCH is PT unscaled — so interpret each series against its own entry. |
| observation_count | No | Total observations in the result. |
| series_attributes | No | Attributes of the first series in the result — the same series as series_metadata[0]. A key with + or * resolves to several series whose scale and unit differ, and this field describes only the first of them: read series_metadata for the rest, and never apply these values to another series_key. |
| retrieval_guidance | No | Present on every staged result. Identifies the imf_dataframe_describe-before-imf_dataframe_query retrieval workflow. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnly/openWorld/idempotent; the description adds substantial non-obvious behavior: a key resolving to several series produces one series_metadata entry per series, valid codes can return no_data, malformed or reversed period ranges are rejected, and large results spill to DataCanvas. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and return shape, then progresses through prerequisites, key syntax, period rules, and spill behavior in a logical order. It is dense and useful, though several sentences restate material already present in the rich input-schema descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers prerequisites, key construction rules, period validation and inclusivity, no_data outcomes, output routing, and the downstream DataCanvas analysis path. With an output schema present for return values, nothing essential for calling the tool correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed parameter descriptions, so baseline is 3. The description adds meaningful extras: the imf_get_database dependency, the code-universe-versus-actual-coverage caveat, and inclusive-bound period semantics. Some key-format and period details duplicate the schema, limiting the additional value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Opens with a specific verb and object — 'Query an IMF SDMX dataflow by dimension key over a time range' — and specifies the return contents (observations with time_period, value, status, unit, scale, decimals). This clearly distinguishes it from sibling metadata and dataframe tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states the prerequisite: 'Requires imf_get_database first to obtain the correct key_format and valid dimension codes.' It also routes large analytical results to imf_dataframe_describe and imf_dataframe_query, giving the agent a clear decision path versus siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
- Changed
imf_get_database11 fields changed- added
Input schema / properties / available_onlyAdded value: +{ + "default": false, + "description": "Return only codes reported by the dataflow-wide availability constraint. Default false keeps ordinary codelist discovery unchanged.", + "type": "boolean" +} - added
Output schema / properties / available_onlyAdded value: +{ + "const": true, + "description": "True when dimensions contain published availability coverage rather than codelists.", + "type": "boolean" +} - changed
Output schema / properties / dimensions / items / descriptionPrevious value: -"A single dimension with its codelist."New value: +"A single dimension with its codelist or published availability coverage." - added
Output schema / properties / dimensions / items / properties / available_countAdded value: +{ + "description": "Codes reported with published data before codelist_filter. Present when available_only is true.", + "type": "number" +} - changed
Output schema / properties / dimensions / items / properties / codelist / descriptionPrevious value: -"Valid codes for this dimension. Unselected previews show up to 50 entries after optional filtering. Select dimension_id and use limit/offset for a bounded page of up to 200 entries. Empty means the filter matched nothing when codelist_filter is echoed back, and that the codelist could not be resolved when it is not — see notice."New value: +"Valid codelist codes for this dimension, or codes reported with published data when available_only is true. Unselected previews show up to 50 entries after optional filtering. Select dimension_id and use limit/offset for a bounded page of up to 200 entries. Empty means the filter matched nothing when codelist_filter is echoed back, no coverage was reported in availability mode, or the codelist could not be resolved in normal mode — see notice." - changed
Output schema / properties / dimensions / items / properties / unfiltered_count / descriptionPrevious value: -"Codes in the complete resolved codelist before codelist_filter is applied."New value: +"Source codes before codelist_filter: the complete resolved codelist normally, or published codes when available_only is true." - changed
Output schema / properties / error / properties / data / properties / reason / descriptionPrevious value: -"Machine-readable failure mode. Declared by this tool: `dataflow_not_found`: dataflow_id does not match any known dataflow on api.imf.org `dimension_not_found`: dimension_id does not match a dimension in the selected dataflow `structure_unavailable`: api.imf.org returns non-200 on the DSD endpoint `dataflow_list_unavailable`: The dataflow catalog that dataflow_id is resolved against could not be fetched — fires before the DSD lookup is attempted Other values are possible when a failure originates below the handler."New value: +"Machine-readable failure mode. Declared by this tool: `dataflow_not_found`: dataflow_id does not match any known dataflow on api.imf.org `dimension_not_found`: dimension_id does not match a dimension in the selected dataflow `structure_unavailable`: api.imf.org returns non-200 on the DSD endpoint `dataflow_list_unavailable`: The dataflow catalog that dataflow_id is resolved against could not be fetched — fires before the DSD lookup is attempted `availability_unavailable`: available_only is true and the dataflow-wide availability constraint cannot be fetched or parsed Other values are possible when a failure originates below the handler." - changed
Output schema / properties / error / properties / data / properties / reason / examplesPrevious value: -[ - "dataflow_not_found", - "dimension_not_found", - "structure_unavailable", - "dataflow_list_unavailable" -]New value: +[ + "dataflow_not_found", + "dimension_not_found", + "structure_unavailable", + "dataflow_list_unavailable", + "availability_unavailable" +] - added
Output schema / properties / series_countAdded value: +{ + "description": "Total series published by the dataflow. Present when available_only is true.", + "type": "number" +} - added
Output schema / properties / time_period_endAdded value: +{ + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Latest period with published data, or null when the constraint omits it." +} - added
Output schema / properties / time_period_startAdded value: +{ + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Earliest period with published data, or null when the constraint omits it." +}
- Changed
imf_list_databases1 field changed- added
Input schema / properties / filter / minLengthAdded value: +1
1 tool update
- Changed
imf_dataframe_query5 fields changed- changed
Output schema / properties / error / properties / data / properties / reason / descriptionPrevious value: -"Machine-readable failure mode. Declared by this tool: `canvas_not_found`: canvas_id does not match any registered DataCanvas session (expired, wrong session, or canvas disabled) `missing_table`: The canvas exists but sql references a table that is not staged on it — the table expired, was dropped, or the name is wrong `invalid_sql`: sql is not a single SELECT statement (a leading WITH … SELECT counts as one), or it is SELECT-shaped but fails to prepare — unknown column, unknown function, or a syntax error `sql_not_permitted`: sql parses as a SELECT but the read-only gate refuses it — it calls an external-data or PRAGMA table function, reads a system catalog, or plans an operator outside the read-only allowlist Other values are possible when a failure originates below the handler."New value: +"Machine-readable failure mode. Declared by this tool: `canvas_not_found`: canvas_id does not match any registered DataCanvas session (expired, wrong session, or canvas disabled) `missing_table`: The canvas exists but sql references a table that is not staged on it — the table expired, was dropped, or the name is wrong `invalid_sql`: sql is not a single SELECT statement (a leading WITH … SELECT counts as one), or it is SELECT-shaped but fails to prepare — unknown column, unknown function, or a syntax error `sql_not_permitted`: sql parses as a SELECT but the read-only gate refuses it — it calls an external-data or PRAGMA table function, reads a system catalog, or plans an operator outside the read-only allowlist `response_too_large`: The first result row cannot fit in the complete structured and formatted response budget Other values are possible when a failure originates below the handler." - changed
Output schema / properties / error / properties / data / properties / reason / examplesPrevious value: -[ - "canvas_not_found", - "missing_table", - "invalid_sql", - "sql_not_permitted" -]New value: +[ + "canvas_not_found", + "missing_table", + "invalid_sql", + "sql_not_permitted", + "response_too_large" +] - changed
Output schema / properties / row_count / descriptionPrevious value: -"Number of rows materialized in rows. Equals the canvas row limit when truncated is true — DataCanvas does not report a pre-cap total, so this is never larger than rows.length."New value: +"Number of materialized rows returned in rows. Always equals rows.length and never claims a pre-cap total." - changed
Output schema / properties / rows / descriptionPrevious value: -"Query result rows, capped at the canvas row limit (default 10,000)."New value: +"Largest result-row prefix whose complete structured and formatted response fits the 100,000-character response budget, after the canvas row limit (default 10,000) is applied." - changed
Output schema / properties / truncated / descriptionPrevious value: -"True when the query matched more rows than the canvas row limit and the result was capped. Page the remainder with a stable ORDER BY plus LIMIT/OFFSET, or narrow the query with WHERE or aggregation."New value: +"True when DataCanvas capped the query at its row limit or the server omitted materialized rows to fit the response-size budget. Page the remainder with a stable ORDER BY plus LIMIT/OFFSET, or narrow the query with WHERE or aggregation."
3 tool updates
- Changed
imf_dataframe_describe1 field changed- changed
Input schema / properties / canvas_id / descriptionPrevious value: -"Canvas ID returned by imf_query_dataset when results were too large for inline delivery."New value: +"Canvas ID returned by imf_query_dataset whenever staged=true, from automatic spillover or output_mode=\"canvas\"."
- Changed
imf_dataframe_query1 field changed- changed
Input schema / properties / canvas_id / descriptionPrevious value: -"Canvas ID returned by imf_query_dataset when results were too large for inline delivery."New value: +"Canvas ID returned by imf_query_dataset whenever staged=true. Call imf_dataframe_describe with it before writing SQL."
- Changed
imf_query_dataset13 fields changed- changed
Input schema / properties / canvas_id / descriptionPrevious value: -"Existing canvas ID to accumulate results into across multiple queries. Omit to allocate a fresh canvas; the response includes a canvas_id when results spill to DataCanvas."New value: +"Existing canvas ID to accumulate results into across multiple queries. This selects the destination only; it does not force staging. Use output_mode=\"canvas\" to stage an under-budget result." - added
Input schema / properties / output_modeAdded value: +{ + "default": "auto", + "description": "Result placement. auto returns an under-budget result inline and spills only when needed. canvas explicitly stages the full result, using canvas_id when supplied or allocating a fresh canvas.", + "enum": [ + "auto", + "canvas" + ], + "type": "string" +} - changed
Input schema / properties / start_period / descriptionPrevious value: -"Start of time range (inclusive). Accepts any of YYYY (annual), YYYY-SN (semi-annual, e.g. 2023-S1), YYYY-QN (quarterly, e.g. 2023-Q1), YYYY-MM (monthly), or YYYY-MM-DD (daily), whatever the dataflow's frequency. The bound covers the whole period it names, so start_period 2023 admits 2023-M01 and 2023-Q1. Observations before this period are excluded from the result."New value: +"Start of time range (inclusive). Accepts any of YYYY (annual), YYYY-SN (semi-annual, e.g. 2023-S1), YYYY-QN (quarterly, e.g. 2023-Q1), YYYY-MM (monthly), or a calendar-valid YYYY-MM-DD (daily), whatever the dataflow's frequency. The bound covers the whole period it names, so start_period 2023 admits 2023-M01 and 2023-Q1. Observations before this period are excluded from the result." - changed
Output schema / anyOfPrevious value: -[ - { - "not": { - "required": [ - "error" - ] - }, - "required": [ - "dataflow_id", - "key", - "observations", - "series_attributes", - "observation_count", - "truncated", - "source" - ] - }, - { - "required": [ - "error" - ] - } -]New value: +[ + { + "not": { + "required": [ + "error" + ] + }, + "required": [ + "dataflow_id", + "key", + "observations", + "series_attributes", + "observation_count", + "staged", + "truncated", + "source" + ] + }, + { + "required": [ + "error" + ] + } +] - changed
Output schema / properties / canvas_id / descriptionPrevious value: -"DataCanvas session ID — present when truncated=true. Pass to imf_dataframe_query or imf_dataframe_describe to query the full result."New value: +"DataCanvas session ID — present when staged=true. Pass first to imf_dataframe_describe, then to imf_dataframe_query." - changed
Output schema / properties / error / properties / data / properties / reason / descriptionPrevious value: -"Machine-readable failure mode. Declared by this tool: `dataflow_not_found`: dataflow_id does not match any known dataflow on api.imf.org `no_data`: Key is structurally valid but the dataflow holds no series for this code combination, or the dataflow publishes no series at all `no_data_in_range`: The key returned observations but start_period/end_period excluded every one of them `key_dimension_mismatch`: Number of dot-separated segments in key does not match the dataflow's DSD dimension count `empty_key_segment`: A dot-separated position in key is empty or blank, which matches no series upstream `invalid_period_format`: start_period or end_period is not one of the recognized period formats `invalid_period_range`: start_period is later than end_period `structure_unavailable`: api.imf.org returns non-200 on the data endpoint `dataflow_list_unavailable`: The dataflow catalog that dataflow_id is resolved against could not be fetched — fires before the DSD and data lookups are attempted Other values are possible when a failure originates below the handler."New value: +"Machine-readable failure mode. Declared by this tool: `dataflow_not_found`: dataflow_id does not match any known dataflow on api.imf.org `no_data`: Key is structurally valid but the dataflow holds no series for this code combination, or the dataflow publishes no series at all `no_data_in_range`: The key returned observations but start_period/end_period excluded every one of them `key_dimension_mismatch`: Number of dot-separated segments in key does not match the dataflow's DSD dimension count `empty_key_segment`: A dot-separated position in key is empty or blank, which matches no series upstream `invalid_period_format`: start_period or end_period is not one of the recognized period formats `invalid_period_range`: start_period is later than end_period `structure_unavailable`: The dataflow structure (DSD) cannot be fetched after the dataflow catalog resolved successfully `canvas_unavailable`: output_mode=\"canvas\" was requested but DataCanvas is disabled `response_too_large`: Fixed staged-result metadata exceeds the response budget before any observation preview can be included `dataflow_list_unavailable`: The dataflow catalog that dataflow_id is resolved against could not be fetched — fires before the DSD and data lookups are attempted Other values are possible when a failure originates below the handler." - changed
Output schema / properties / error / properties / data / properties / reason / examplesPrevious value: -[ - "dataflow_not_found", - "no_data", - "no_data_in_range", - "key_dimension_mismatch", - "empty_key_segment", - "invalid_period_format", - "invalid_period_range", - "structure_unavailable", - "dataflow_list_unavailable" -]New value: +[ + "dataflow_not_found", + "no_data", + "no_data_in_range", + "key_dimension_mismatch", + "empty_key_segment", + "invalid_period_format", + "invalid_period_range", + "structure_unavailable", + "canvas_unavailable", + "response_too_large", + "dataflow_list_unavailable" +] - changed
Output schema / properties / notice / descriptionPrevious value: -"Populated when a period bound was set but some observations carry a time_period label the range filter does not recognize — those rows are returned unfiltered, so the requested range did not apply to them."New value: +"Populated when a period bound was set but some observations carry a time_period label the range filter does not recognize. Composes with staged retrieval_guidance when both apply." - changed
Output schema / properties / observations / descriptionPrevious value: -"Inline observations. Empty when results spilled to canvas (see canvas_id / table_name)."New value: +"Inline observation preview. For staged results this may contain the full set or a budget-limited prefix; observation_count remains the full count." - added
Output schema / properties / retrieval_guidanceAdded value: +{ + "description": "Present on every staged result. Identifies the imf_dataframe_describe-before-imf_dataframe_query retrieval workflow.", + "type": "string" +} - added
Output schema / properties / stagedAdded value: +{ + "description": "True when the complete observation set is stored on DataCanvas. canvas_id and table_name are present whenever true.", + "type": "boolean" +} - changed
Output schema / properties / table_name / descriptionPrevious value: -"DuckDB table name on the canvas — present when truncated=true; reference in SQL via FROM <table_name>."New value: +"DuckDB table name on the canvas — present when staged=true; reference in SQL via FROM <table_name>." - changed
Output schema / properties / truncated / descriptionPrevious value: -"True when the result exceeded the inline limit and was staged on a DataCanvas table; canvas_id and table_name are populated and imf_dataframe_query provides SQL access to the full set."New value: +"True only when observations is an incomplete preview of observation_count. A result can be staged=true and truncated=false when every observation also fits inline."
1 tool update
- Changed
imf_get_database20 fields changed- changed
Input schema / properties / codelist_filter / descriptionPrevious value: -"Optional case-insensitive substring to search within each dimension's codelist (code ID and name). When set, returns all matching entries per dimension instead of the first-50 window — useful for large codelists like WEO INDICATOR (145 entries). Example: \"CPI\" or \"PCPIPCH\" surfaces consumer price index codes without hitting the 50-entry cap."New value: +"Optional case-insensitive substring to search within each dimension's codelist (code ID and name). Filtering runs before the 50-entry preview or selected-dimension page. Example: \"CPI\" or \"Constant prices\" surfaces matching WEO indicator codes." - added
Input schema / properties / codelist_filter / minLengthAdded value: +1 - added
Input schema / properties / dimension_idAdded value: +{ + "description": "Exact dimension ID from this tool, e.g. INDICATOR. Select one dimension to page beyond its preview.", + "minLength": 1, + "type": "string" +} - added
Input schema / properties / limitAdded value: +{ + "description": "Entries to return from the selected dimension. Valid only with dimension_id; default 50, maximum 200.", + "maximum": 200, + "minimum": 1, + "type": "integer" +} - added
Input schema / properties / offsetAdded value: +{ + "description": "Matching entries to skip in the selected dimension before this page. Valid only with dimension_id; default 0.", + "maximum": 9007199254740991, + "minimum": 0, + "type": "integer" +} - changed
Output schema / anyOfPrevious value: -[ - { - "not": { - "required": [ - "error" - ] - }, - "required": [ - "dataflow_id", - "agency_id", - "version", - "name", - "key_format", - "dimensions", - "source" - ] - }, - { - "required": [ - "error" - ] - } -]New value: +[ + { + "not": { + "required": [ + "error" + ] + }, + "required": [ + "dataflow_id", + "agency_id", + "version", + "name", + "key_format", + "truncated", + "dimensions", + "source" + ] + }, + { + "required": [ + "error" + ] + } +] - added
Output schema / properties / dimension_idAdded value: +{ + "description": "Selected dimension ID. Absent when previews for every dimension were returned.", + "type": "string" +} - changed
Output schema / properties / dimensions / descriptionPrevious value: -"All dimensions of this dataflow with their codelists."New value: +"All dimension previews, or the one selected dimension page." - changed
Output schema / properties / dimensions / items / properties / codelist / descriptionPrevious value: -"Valid codes for this dimension. Up to 50 entries shown when no codelist_filter is set; use codelist_filter to search large codelists or the imf://database resource for the full list. Empty means the filter matched nothing when codelist_filter is echoed back, and that the codelist could not be resolved when it is not — see notice."New value: +"Valid codes for this dimension. Unselected previews show up to 50 entries after optional filtering. Select dimension_id and use limit/offset for a bounded page of up to 200 entries. Empty means the filter matched nothing when codelist_filter is echoed back, and that the codelist could not be resolved when it is not — see notice." - changed
Output schema / properties / dimensions / items / properties / codelist_truncated / descriptionPrevious value: -"True when the codelist has more than 50 entries and was truncated."New value: +"True when matching codes were omitted before or after this page." - added
Output schema / properties / dimensions / items / properties / matched_countAdded value: +{ + "description": "Codes matching codelist_filter before limit and offset are applied.", + "type": "number" +} - added
Output schema / properties / dimensions / items / properties / next_offsetAdded value: +{ + "description": "Offset for the next page when later matching codes remain.", + "type": "number" +} - added
Output schema / properties / dimensions / items / properties / offsetAdded value: +{ + "description": "Matching codes skipped before this dimension page.", + "type": "number" +} - added
Output schema / properties / dimensions / items / properties / returned_countAdded value: +{ + "description": "Codes returned in this dimension page.", + "type": "number" +} - added
Output schema / properties / dimensions / items / properties / unfiltered_countAdded value: +{ + "description": "Codes in the complete resolved codelist before codelist_filter is applied.", + "type": "number" +} - changed
Output schema / properties / dimensions / items / requiredPrevious value: -[ - "id", - "name", - "position", - "codelist", - "codelist_truncated" -]New value: +[ + "id", + "name", + "position", + "codelist", + "codelist_truncated", + "unfiltered_count", + "matched_count", + "returned_count", + "offset" +] - changed
Output schema / properties / error / properties / data / properties / reason / descriptionPrevious value: -"Machine-readable failure mode. Declared by this tool: `dataflow_not_found`: dataflow_id does not match any known dataflow on api.imf.org `structure_unavailable`: api.imf.org returns non-200 on the DSD endpoint `dataflow_list_unavailable`: The dataflow catalog that dataflow_id is resolved against could not be fetched — fires before the DSD lookup is attempted Other values are possible when a failure originates below the handler."New value: +"Machine-readable failure mode. Declared by this tool: `dataflow_not_found`: dataflow_id does not match any known dataflow on api.imf.org `dimension_not_found`: dimension_id does not match a dimension in the selected dataflow `structure_unavailable`: api.imf.org returns non-200 on the DSD endpoint `dataflow_list_unavailable`: The dataflow catalog that dataflow_id is resolved against could not be fetched — fires before the DSD lookup is attempted Other values are possible when a failure originates below the handler." - changed
Output schema / properties / error / properties / data / properties / reason / examplesPrevious value: -[ - "dataflow_not_found", - "structure_unavailable", - "dataflow_list_unavailable" -]New value: +[ + "dataflow_not_found", + "dimension_not_found", + "structure_unavailable", + "dataflow_list_unavailable" +] - changed
Output schema / properties / notice / descriptionPrevious value: -"Populated when a codelist_filter matched no entries anywhere, or when a dimension has no resolvable codelist — the two produce the same empty array and need opposite next steps."New value: +"Populated when a codelist_filter matched no entries anywhere, or when a dimension has no resolvable codelist, or when offset is past the final match." - added
Output schema / properties / truncatedAdded value: +{ + "description": "True when any returned dimension page omits matching codes.", + "type": "boolean" +}
5 tool updates
- Changed
imf_dataframe_describe6 fields changed- changed
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Input schema / additionalPropertiesAdded value: +false - changed
Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Output schema / anyOfAdded value: +[ + { + "not": { + "required": [ + "error" + ] + }, + "required": [ + "canvas_id", + "tables", + "table_count" + ] + }, + { + "required": [ + "error" + ] + } +] - added
Output schema / properties / errorAdded value: +{ + "additionalProperties": {}, + "description": "Present when the call failed. Absent on success.", + "properties": { + "code": { + "description": "JSON-RPC error code for this failure.", + "maximum": 9007199254740991, + "minimum": -9007199254740991, + "type": "integer" + }, + "data": { + "additionalProperties": {}, + "properties": { + "reason": { + "description": "Machine-readable failure mode. Declared by this tool: `canvas_not_found`: canvas_id does not match any registered DataCanvas session (expired, wrong session, or canvas disabled) Other values are possible when a failure originates below the handler.", + "examples": [ + "canvas_not_found" + ], + "type": "string" + }, + "recovery": { + "additionalProperties": {}, + "description": "Actionable next step for the caller.", + "properties": { + "hint": { + "type": "string" + } + }, + "required": [ + "hint" + ], + "type": "object" + }, + "retryable": { + "description": "Whether retrying may succeed.", + "type": "boolean" + } + }, + "type": "object" + }, + "message": { + "description": "Human-readable description of what went wrong.", + "type": "string" + } + }, + "required": [ + "code", + "message" + ], + "type": "object" +} - removed
Output schema / requiredRemoved value: -[ - "canvas_id", - "tables", - "table_count" -]
- Changed
imf_dataframe_query6 fields changed- changed
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Input schema / additionalPropertiesAdded value: +false - changed
Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Output schema / anyOfAdded value: +[ + { + "not": { + "required": [ + "error" + ] + }, + "required": [ + "rows", + "row_count", + "truncated" + ] + }, + { + "required": [ + "error" + ] + } +] - added
Output schema / properties / errorAdded value: +{ + "additionalProperties": {}, + "description": "Present when the call failed. Absent on success.", + "properties": { + "code": { + "description": "JSON-RPC error code for this failure.", + "maximum": 9007199254740991, + "minimum": -9007199254740991, + "type": "integer" + }, + "data": { + "additionalProperties": {}, + "properties": { + "reason": { + "description": "Machine-readable failure mode. Declared by this tool: `canvas_not_found`: canvas_id does not match any registered DataCanvas session (expired, wrong session, or canvas disabled) `missing_table`: The canvas exists but sql references a table that is not staged on it — the table expired, was dropped, or the name is wrong `invalid_sql`: sql is not a single SELECT statement (a leading WITH … SELECT counts as one), or it is SELECT-shaped but fails to prepare — unknown column, unknown function, or a syntax error `sql_not_permitted`: sql parses as a SELECT but the read-only gate refuses it — it calls an external-data or PRAGMA table function, reads a system catalog, or plans an operator outside the read-only allowlist Other values are possible when a failure originates below the handler.", + "examples": [ + "canvas_not_found", + "missing_table", + "invalid_sql", + "sql_not_permitted" + ], + "type": "string" + }, + "recovery": { + "additionalProperties": {}, + "description": "Actionable next step for the caller.", + "properties": { + "hint": { + "type": "string" + } + }, + "required": [ + "hint" + ], + "type": "object" + }, + "retryable": { + "description": "Whether retrying may succeed.", + "type": "boolean" + } + }, + "type": "object" + }, + "message": { + "description": "Human-readable description of what went wrong.", + "type": "string" + } + }, + "required": [ + "code", + "message" + ], + "type": "object" +} - removed
Output schema / requiredRemoved value: -[ - "rows", - "row_count", - "truncated" -]
- Changed
imf_get_database6 fields changed- changed
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Input schema / additionalPropertiesAdded value: +false - changed
Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Output schema / anyOfAdded value: +[ + { + "not": { + "required": [ + "error" + ] + }, + "required": [ + "dataflow_id", + "agency_id", + "version", + "name", + "key_format", + "dimensions", + "source" + ] + }, + { + "required": [ + "error" + ] + } +] - added
Output schema / properties / errorAdded value: +{ + "additionalProperties": {}, + "description": "Present when the call failed. Absent on success.", + "properties": { + "code": { + "description": "JSON-RPC error code for this failure.", + "maximum": 9007199254740991, + "minimum": -9007199254740991, + "type": "integer" + }, + "data": { + "additionalProperties": {}, + "properties": { + "reason": { + "description": "Machine-readable failure mode. Declared by this tool: `dataflow_not_found`: dataflow_id does not match any known dataflow on api.imf.org `structure_unavailable`: api.imf.org returns non-200 on the DSD endpoint `dataflow_list_unavailable`: The dataflow catalog that dataflow_id is resolved against could not be fetched — fires before the DSD lookup is attempted Other values are possible when a failure originates below the handler.", + "examples": [ + "dataflow_not_found", + "structure_unavailable", + "dataflow_list_unavailable" + ], + "type": "string" + }, + "recovery": { + "additionalProperties": {}, + "description": "Actionable next step for the caller.", + "properties": { + "hint": { + "type": "string" + } + }, + "required": [ + "hint" + ], + "type": "object" + }, + "retryable": { + "description": "Whether retrying may succeed.", + "type": "boolean" + } + }, + "type": "object" + }, + "message": { + "description": "Human-readable description of what went wrong.", + "type": "string" + } + }, + "required": [ + "code", + "message" + ], + "type": "object" +} - removed
Output schema / requiredRemoved value: -[ - "dataflow_id", - "agency_id", - "version", - "name", - "key_format", - "dimensions", - "source" -]
- Changed
imf_list_databases6 fields changed- changed
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Input schema / additionalPropertiesAdded value: +false - changed
Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Output schema / anyOfAdded value: +[ + { + "not": { + "required": [ + "error" + ] + }, + "required": [ + "dataflows", + "total_count", + "returned_count", + "offset" + ] + }, + { + "required": [ + "error" + ] + } +] - added
Output schema / properties / errorAdded value: +{ + "additionalProperties": {}, + "description": "Present when the call failed. Absent on success.", + "properties": { + "code": { + "description": "JSON-RPC error code for this failure.", + "maximum": 9007199254740991, + "minimum": -9007199254740991, + "type": "integer" + }, + "data": { + "additionalProperties": {}, + "properties": { + "reason": { + "description": "Machine-readable failure mode. Declared by this tool: `dataflow_list_unavailable`: The IMF SDMX structure endpoint that backs the dataflow catalog did not return a usable response Other values are possible when a failure originates below the handler.", + "examples": [ + "dataflow_list_unavailable" + ], + "type": "string" + }, + "recovery": { + "additionalProperties": {}, + "description": "Actionable next step for the caller.", + "properties": { + "hint": { + "type": "string" + } + }, + "required": [ + "hint" + ], + "type": "object" + }, + "retryable": { + "description": "Whether retrying may succeed.", + "type": "boolean" + } + }, + "type": "object" + }, + "message": { + "description": "Human-readable description of what went wrong.", + "type": "string" + } + }, + "required": [ + "code", + "message" + ], + "type": "object" +} - removed
Output schema / requiredRemoved value: -[ - "dataflows", - "total_count", - "returned_count", - "offset" -]
- Changed
imf_query_dataset6 fields changed- changed
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Input schema / additionalPropertiesAdded value: +false - changed
Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema" - added
Output schema / anyOfAdded value: +[ + { + "not": { + "required": [ + "error" + ] + }, + "required": [ + "dataflow_id", + "key", + "observations", + "series_attributes", + "observation_count", + "truncated", + "source" + ] + }, + { + "required": [ + "error" + ] + } +] - added
Output schema / properties / errorAdded value: +{ + "additionalProperties": {}, + "description": "Present when the call failed. Absent on success.", + "properties": { + "code": { + "description": "JSON-RPC error code for this failure.", + "maximum": 9007199254740991, + "minimum": -9007199254740991, + "type": "integer" + }, + "data": { + "additionalProperties": {}, + "properties": { + "reason": { + "description": "Machine-readable failure mode. Declared by this tool: `dataflow_not_found`: dataflow_id does not match any known dataflow on api.imf.org `no_data`: Key is structurally valid but the dataflow holds no series for this code combination, or the dataflow publishes no series at all `no_data_in_range`: The key returned observations but start_period/end_period excluded every one of them `key_dimension_mismatch`: Number of dot-separated segments in key does not match the dataflow's DSD dimension count `empty_key_segment`: A dot-separated position in key is empty or blank, which matches no series upstream `invalid_period_format`: start_period or end_period is not one of the recognized period formats `invalid_period_range`: start_period is later than end_period `structure_unavailable`: api.imf.org returns non-200 on the data endpoint `dataflow_list_unavailable`: The dataflow catalog that dataflow_id is resolved against could not be fetched — fires before the DSD and data lookups are attempted Other values are possible when a failure originates below the handler.", + "examples": [ + "dataflow_not_found", + "no_data", + "no_data_in_range", + "key_dimension_mismatch", + "empty_key_segment", + "invalid_period_format", + "invalid_period_range", + "structure_unavailable", + "dataflow_list_unavailable" + ], + "type": "string" + }, + "recovery": { + "additionalProperties": {}, + "description": "Actionable next step for the caller.", + "properties": { + "hint": { + "type": "string" + } + }, + "required": [ + "hint" + ], + "type": "object" + }, + "retryable": { + "description": "Whether retrying may succeed.", + "type": "boolean" + } + }, + "type": "object" + }, + "message": { + "description": "Human-readable description of what went wrong.", + "type": "string" + } + }, + "required": [ + "code", + "message" + ], + "type": "object" +} - removed
Output schema / requiredRemoved value: -[ - "dataflow_id", - "key", - "observations", - "series_attributes", - "observation_count", - "truncated", - "source" -]
1 tool update
- Changed
imf_query_dataset3 fields changed- changed
Output schema / properties / series_attributes / properties / unit / descriptionPrevious value: -"Unit of measure, e.g. Percent, USD."New value: +"Unit of measure as the upstream code, e.g. PT (percent), USD, XDC (domestic currency), NUM (count). Null when the response carries no unit for the series — many dataflows publish none." - changed
Output schema / properties / series_metadata / descriptionPrevious value: -"Per-series attributes, one entry per distinct series_key in the result. Present only when the query resolved to more than one series; a single-series query carries its values in series_attributes instead. Scale differs across series in one query — WEO NGDPD is scale 9 while NGDP_RPCH is unscaled — so interpret each series against its own entry."New value: +"Per-series attributes, one entry per distinct series_key in the result. Present only when the query resolved to more than one series; a single-series query carries its values in series_attributes instead. Unit and scale differ across series in one query — WEO NGDPD is USD at scale 9 while NGDP_RPCH is PT unscaled — so interpret each series against its own entry." - changed
Output schema / properties / series_metadata / items / properties / unit / descriptionPrevious value: -"Unit of measure for this series, e.g. Percent."New value: +"Unit of measure for this series as the upstream code, e.g. PT (percent), USD, XDC (domestic currency). Null when the response carries none for it."
3 tool updates
- Changed
imf_get_database1 field changed- changed
Output schema / properties / description / descriptionPrevious value: -"This dataflow's own description, matching what imf_list_databases reports for the same id — not the shared DSD's. Absent when the dataflow publishes none."New value: +"This dataflow's own description in full — not the shared DSD's, and not the shortened preview imf_list_databases returns for the same id. Absent when the dataflow publishes none."
- Changed
imf_list_databases12 fields changed- added
Input schema / properties / limitAdded value: +{ + "default": 50, + "description": "Maximum dataflows to return in this call. Default 50, ceiling 200; total_count reports how many matched, so a partial page is always recognizable as one.", + "maximum": 200, + "minimum": 1, + "type": "integer" +} - added
Input schema / properties / offsetAdded value: +{ + "default": 0, + "description": "Number of matching dataflows to skip before this page. Combine with limit to page through a broad or unfiltered catalog.", + "maximum": 9007199254740991, + "minimum": 0, + "type": "integer" +} - added
Output schema / properties / capAdded value: +{ + "description": "The limit that bounded this page.", + "type": "number" +} - changed
Output schema / properties / dataflows / descriptionPrevious value: -"Matching dataflows; pass the id to imf_get_database to resolve dimension codelists."New value: +"This page of matching dataflows; pass the id to imf_get_database to resolve dimension codelists." - changed
Output schema / properties / dataflows / items / properties / description / descriptionPrevious value: -"Extended description of the dataflow, if available."New value: +"Short description, cut to 200 characters and ended with … when longer. imf_get_database and the imf://database/{dataflow_id} resource return the full text." - changed
Output schema / properties / notice / descriptionPrevious value: -"Populated when the filter matches nothing — explains why and suggests next steps."New value: +"Populated when the filter matches nothing, or when matches remain beyond this page — explains why and names the next offset to request." - added
Output schema / properties / offsetAdded value: +{ + "description": "Number of matching dataflows skipped before this page.", + "type": "number" +} - added
Output schema / properties / returned_countAdded value: +{ + "description": "Dataflows in this page — the length of dataflows.", + "type": "number" +} - added
Output schema / properties / shownAdded value: +{ + "description": "Dataflows returned in this page.", + "type": "number" +} - changed
Output schema / properties / total_count / descriptionPrevious value: -"Total number of matching dataflows returned."New value: +"Dataflows matching filter and include_vintages, before limit and offset are applied. Exceeds returned_count when more pages remain." - added
Output schema / properties / truncatedAdded value: +{ + "description": "True when matching dataflows remain beyond this page.", + "type": "boolean" +} - changed
Output schema / requiredPrevious value: -[ - "dataflows", - "total_count" -]New value: +[ + "dataflows", + "total_count", + "returned_count", + "offset" +]
- Changed
imf_query_dataset3 fields changed- changed
Output schema / properties / series_attributes / descriptionPrevious value: -"Series-level attributes (unit, scale, decimals)."New value: +"Attributes of the first series in the result — the same series as series_metadata[0]. A key with + or * resolves to several series whose scale and unit differ, and this field describes only the first of them: read series_metadata for the rest, and never apply these values to another series_key." - changed
Output schema / properties / series_attributes / properties / scale / descriptionPrevious value: -"Scale multiplier, e.g. Billions."New value: +"Scale multiplier as the upstream code, e.g. 9 for billions. \"0\" means no multiplier — the values are unscaled." - added
Output schema / properties / series_metadataAdded value: +{ + "description": "Per-series attributes, one entry per distinct series_key in the result. Present only when the query resolved to more than one series; a single-series query carries its values in series_attributes instead. Scale differs across series in one query — WEO NGDPD is scale 9 while NGDP_RPCH is unscaled — so interpret each series against its own entry.", + "items": { + "additionalProperties": false, + "description": "Unit, scale, and decimals for one series in the result.", + "properties": { + "decimals": { + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "description": "Number of decimal places shown for this series." + }, + "scale": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Scale multiplier for this series as the upstream code, e.g. 9 for billions. \"0\" means no multiplier." + }, + "series_key": { + "description": "Series these attributes belong to, matching observations[].series_key.", + "type": "string" + }, + "unit": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Unit of measure for this series, e.g. Percent." + } + }, + "required": [ + "series_key", + "unit", + "scale", + "decimals" + ], + "type": "object" + }, + "type": "array" +}
2 tool updates
- Changed
imf_get_database1 field changed- changed
Output schema / properties / description / descriptionPrevious value: -"Extended description, if available."New value: +"This dataflow's own description, matching what imf_list_databases reports for the same id — not the shared DSD's. Absent when the dataflow publishes none."
- Changed
imf_query_dataset5 fields changed- changed
Input schema / properties / end_period / descriptionPrevious value: -"End of time range (inclusive). Same format as start_period, and must be greater than or equal to start_period. Observations after this period are excluded from the result."New value: +"End of time range (inclusive). Same formats as start_period, and must not be earlier than it. The bound covers the whole period it names, so end_period 2023 admits 2023-M12 and 2023-Q4. Observations after this period are excluded from the result." - changed
Input schema / properties / key / descriptionPrevious value: -"Dot-separated dimension codes in DSD keyPosition order. Call imf_get_database to get key_format and valid codes first. Use + to specify multiple codes (e.g. USA+GBR.NGDP_RPCH.A). Country codes are ISO 3-letter: USA not US, GBR not GB, DEU not DE."New value: +"Dot-separated dimension codes in DSD keyPosition order. Call imf_get_database to get key_format and valid codes first. Use + to combine codes at one position (e.g. USA+GBR.NGDP_RPCH.A). Use * to match every code at a position — *.NGDP_RPCH.A returns the indicator for all countries, and CAN.*.A every indicator for Canada. Every position needs a code or a *; an empty segment (USA..A) is rejected. Country codes are ISO 3-letter: USA not US, GBR not GB, DEU not DE." - changed
Input schema / properties / start_period / descriptionPrevious value: -"Start of time range (inclusive). Format matches the dataflow frequency: YYYY (annual), YYYY-QN (quarterly, e.g. 2023-Q1), YYYY-MM (monthly). Observations before this period are excluded from the result."New value: +"Start of time range (inclusive). Accepts any of YYYY (annual), YYYY-SN (semi-annual, e.g. 2023-S1), YYYY-QN (quarterly, e.g. 2023-Q1), YYYY-MM (monthly), or YYYY-MM-DD (daily), whatever the dataflow's frequency. The bound covers the whole period it names, so start_period 2023 admits 2023-M01 and 2023-Q1. Observations before this period are excluded from the result." - added
Output schema / properties / noticeAdded value: +{ + "description": "Populated when a period bound was set but some observations carry a time_period label the range filter does not recognize — those rows are returned unfiltered, so the requested range did not apply to them.", + "type": "string" +} - changed
Output schema / properties / observations / items / properties / time_period / descriptionPrevious value: -"Time label as emitted by the upstream API. Annual: YYYY (e.g. 2023). Quarterly: YYYY-QN (e.g. 2023-Q1). Monthly: YYYY-MNN (e.g. 2023-M01, not YYYY-MM). start_period/end_period accept both YYYY-MM and YYYY-MNN for monthly comparisons."New value: +"Time label as emitted by the upstream API. Annual: YYYY (e.g. 2023). Semi-annual: YYYY-SN (e.g. 2023-S1). Quarterly: YYYY-QN (e.g. 2023-Q1). Monthly: YYYY-MNN (e.g. 2023-M01, not YYYY-MM). Daily: YYYY-MM-DD (e.g. 2023-01-05). Every one of these is also accepted as a start_period/end_period bound, so a label from this field can be passed straight back in."
1 tool update
- Changed
imf_get_database4 fields changed- added
Output schema / properties / codelist_filterAdded value: +{ + "description": "Echo of the codelist_filter that produced this result. Absent when no filter was applied — an empty codelist then means the codelist could not be resolved, not that the filter missed.", + "type": "string" +} - changed
Output schema / properties / dimensions / items / properties / codelist / descriptionPrevious value: -"Valid codes for this dimension. Up to 50 entries shown when no codelist_filter is set; use codelist_filter to search large codelists or the imf://database resource for the full list."New value: +"Valid codes for this dimension. Up to 50 entries shown when no codelist_filter is set; use codelist_filter to search large codelists or the imf://database resource for the full list. Empty means the filter matched nothing when codelist_filter is echoed back, and that the codelist could not be resolved when it is not — see notice." - changed
Output schema / properties / dimensions / items / properties / name / descriptionPrevious value: -"Human-readable dimension name."New value: +"Human-readable dimension label from the DSD concept scheme, e.g. Weight Type for WGT_TYPE. Falls back to the dimension id when the structure names no concept." - added
Output schema / properties / noticeAdded value: +{ + "description": "Populated when a codelist_filter matched no entries anywhere, or when a dimension has no resolvable codelist — the two produce the same empty array and need opposite next steps.", + "type": "string" +}
1 tool update
- Changed
imf_dataframe_query4 fields changed- changed
Input schema / properties / sql / descriptionPrevious value: -"Read-only SQL SELECT statement. Must start with SELECT. Reference tables by the names returned by imf_dataframe_describe. Example: SELECT time_period, value FROM spilled_abc123 WHERE time_period >= '2010' ORDER BY time_period."New value: +"Read-only SQL SELECT statement — exactly one statement, starting with SELECT or with a WITH … SELECT common table expression. Reference tables by the names returned by imf_dataframe_describe. Example: SELECT time_period, value FROM spilled_abc123 WHERE time_period >= '2010' ORDER BY time_period." - changed
Output schema / properties / row_count / descriptionPrevious value: -"Total matching rows before the cap — may exceed rows.length."New value: +"Number of rows materialized in rows. Equals the canvas row limit when truncated is true — DataCanvas does not report a pre-cap total, so this is never larger than rows.length." - added
Output schema / properties / truncatedAdded value: +{ + "description": "True when the query matched more rows than the canvas row limit and the result was capped. Page the remainder with a stable ORDER BY plus LIMIT/OFFSET, or narrow the query with WHERE or aggregation.", + "type": "boolean" +} - changed
Output schema / requiredPrevious value: -[ - "rows", - "row_count" -]New value: +[ + "rows", + "row_count", + "truncated" +]
1 tool update
- Changed
imf_query_dataset1 field changed- changed
Input schema / properties / end_period / descriptionPrevious value: -"End of time range (inclusive). Same format as start_period. Observations after this period are excluded from the result."New value: +"End of time range (inclusive). Same format as start_period, and must be greater than or equal to start_period. Observations after this period are excluded from the result."
1 tool update
- Changed
imf_get_database2 fields changed- added
Output schema / properties / dsd_versionAdded value: +{ + "description": "Version of the underlying data structure definition (DSD) that backs this dataflow. Differs from version when the dataflow references a shared DSD (e.g. IIP → DSD_BOP at 24.0.0).", + "type": "string" +} - added
Output schema / properties / structure_refAdded value: +{ + "description": "Identifier of the underlying DSD, e.g. DSD_BOP. Several dataflows can share one DSD.", + "type": "string" +}
3 tool updates
- Changed
imf_get_database2 fields changed- added
Input schema / properties / codelist_filterAdded value: +{ + "description": "Optional case-insensitive substring to search within each dimension's codelist (code ID and name). When set, returns all matching entries per dimension instead of the first-50 window — useful for large codelists like WEO INDICATOR (145 entries). Example: \"CPI\" or \"PCPIPCH\" surfaces consumer price index codes without hitting the 50-entry cap.", + "type": "string" +} - changed
Output schema / properties / dimensions / items / properties / codelist / descriptionPrevious value: -"Valid codes for this dimension. Up to 50 entries shown; full list available via the imf://database resource."New value: +"Valid codes for this dimension. Up to 50 entries shown when no codelist_filter is set; use codelist_filter to search large codelists or the imf://database resource for the full list."
- Changed
imf_list_databases1 field changed- changed
Input schema / properties / filter / descriptionPrevious value: -"Optional name or ID substring to filter results. Case-insensitive. Example: \"exchange rate\" returns ER and related dataflows."New value: +"Optional name, ID, or description substring to filter results. Case-insensitive. Example: \"exchange rate\" returns ER and related dataflows."
- Changed
imf_query_dataset3 fields changed- changed
Input schema / properties / end_period / descriptionPrevious value: -"Requested end of time range. Same format as start_period. See start_period note: the API returns the full series; this parameter is passed through but may not filter observations."New value: +"End of time range (inclusive). Same format as start_period. Observations after this period are excluded from the result." - changed
Input schema / properties / start_period / descriptionPrevious value: -"Requested start of time range. Format matches the dataflow frequency: YYYY (annual), YYYY-QN (quarterly, e.g. 2023-Q1), YYYY-MM (monthly). Note: the IMF SDMX 3.0 compact JSON endpoint returns the full available series regardless of this parameter — observations outside the requested range may still appear."New value: +"Start of time range (inclusive). Format matches the dataflow frequency: YYYY (annual), YYYY-QN (quarterly, e.g. 2023-Q1), YYYY-MM (monthly). Observations before this period are excluded from the result." - changed
Output schema / properties / observations / items / properties / time_period / descriptionPrevious value: -"Time label, e.g. 2023 or 2023-Q1 or 2023-01."New value: +"Time label as emitted by the upstream API. Annual: YYYY (e.g. 2023). Quarterly: YYYY-QN (e.g. 2023-Q1). Monthly: YYYY-MNN (e.g. 2023-M01, not YYYY-MM). start_period/end_period accept both YYYY-MM and YYYY-MNN for monthly comparisons."
5 tool updates
- First observed
imf_dataframe_describe - First observed
imf_dataframe_query - First observed
imf_get_database - First observed
imf_list_databases - First observed
imf_query_dataset
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Connectors
IMF MCP — wraps IMF SDMX JSON REST API (dataservices.imf.org)
Macro indicators from World Bank, FRED, IMF, and OECD via unified query surface.
Search and query 1,500+ OECD statistical datasets via SDMX. Keyless.
Query 29,500+ World Bank development indicators for 200+ countries across 60+ years.
Related MCP Servers
- AlicenseNot gradedqualityAmaintenanceEnables searching, exploring, and querying over 1,500 OECD statistical datasets via SDMX, covering national accounts, employment, trade, PISA, health, and more.2892Apache 2.0

@pipeworx/bisofficial
AlicenseNot gradedqualityCmaintenanceEnables querying Bank for International Settlements central-bank and global financial statistics via the SDMX v2 API, including credit-to-GDP gaps, curated dataflows, and full registry search with dataset fetching, without authentication.41MIT- AlicenseNot gradedqualityCmaintenanceProvides access to European Central Bank statistical data through SDMX data flows, enabling querying and listing of data flows via natural language or direct tool calls.6MIT
- AlicenseNot gradedqualityCmaintenanceEnables discovery and retrieval of National Bank of Belgium statistical data across 221 SDMX dataflows, with search, descriptions, custom queries, and comparisons of economic indicators.3MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
Each tool has a clearly distinct role: discovering dataflows, inspecting dimensions/codelists, querying SDMX data, and analyzing staged DataCanvas tables. The two query-like tools are separated by their data source (live SDMX vs. staged results), and the descriptions reinforce the required sequencing.
The imf_ prefix and snake_case convention are consistent, and most tools follow verb_noun naming (list_databases, get_database, query_dataset). However, imf_dataframe_describe and imf_dataframe_query place the object before the verb, deviating slightly from the otherwise predictable pattern.
Five tools is well-scoped for a read-only IMF data access server. Each tool covers a necessary stage in the workflow without redundancy or bloat.
The tool set covers the full read-only lifecycle: discover dataflows, inspect required dimension codes, query series, and analyze large result sets via SQL. No obvious gaps exist for the stated purpose, and write operations are not relevant to this domain.