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Glama

Ecb

by io.github.pipeworx-io

Ecb Get Data

ecb_get_data
Read-onlyIdempotent

Generic SDMX data fetch from any ECB flow. Key is dot-separated dimension values; empty positions are wildcards. Example: flow_ref="EXR", key="D.USD.EUR.SP00.A" (daily USD/EUR spot).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesSeries key, dot-separated dimension values
last_nNoReturn only the last N observations
flow_refYesFlow reference — EXR (exchange rates), ICP (HICP), BSI, IRS, STS, BLS, MIR, ...
end_periodNoEnd date / period
start_periodNoStart date / period

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "flow_ref": "EXR",
+    "key": "D.USD.EUR.SP00.A"
+  },
+  {
+    "flow_ref": "ICP",
+    "key": "M.DE.....CP00",
+    "last_n": 12,
+    "start_period": "2023-01"
+  }
+]
  2. Added

TDQS

A4.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and non-destructive. The description adds minimal behavioral detail beyond the example usage, which is consistent 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with a concise example, no wasted words. The information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters all described in schema and no output schema, the description provides sufficient context for typical usage, but could briefly mention the return format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds meaningful explanation of the key parameter (dot-separated, wildcards) and lists example flow_ref values, providing context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Generic SDMX data fetch from any ECB flow', specifying the verb and resource. It distinguishes from siblings like ecb_exchange_rate and ecb_hicp_inflation which are specific tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an example and explains the key format, implying use for generic ECB data. However, it does not explicitly state when to use this tool versus specific siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation2/5

There is significant overlap between tool clusters: ask_pipeworx_beta is currently functionally identical to ask_pipeworx, and polymarket_arbitrage/polymarket_edges/bet_research all target similar opportunity-discovery tasks. While the descriptions are extremely detailed, the sheer number of similar variants makes it hard to reliably pick the right one.

Naming Consistency4/5

Names are consistently snake_case with meaningful prefixes (ask_, ecb_, polymarket_, pipeworx_) and mostly verb-first structure. Minor deviations like entity_profile and ecb_hicp_inflation are noun-first, but they do not break the overall pattern.

Tool Count2/5

35 tools is well beyond the well-scoped 3–15 range, and the surface feels bloated with redundant meta-tools (ask_pipeworx variants, deep_research, discover_tools, suggest_questions) and peripheral utilities like generate_llms_txt and scan_dependency. Many entries could be consolidated without losing function.

Completeness4/5

For the server's broad data-research domain, coverage is thoughtful and full: query, grounded answer, validation, entity resolution, profiling, comparative analysis, subscription lifecycle, memory, and feedback are all represented. Minor gaps exist (e.g., no direct raw ECB flow browser beyond generic SDMX) but nothing blocking.

Resources