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Glama

timezone

by io.github.pipeworx-io

Resolve Entity

resolve_entity
Read-onlyIdempotent

"What's the ticker for…" / "find the CIK for…" / "what's the LEI for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" / "who owns X" / "is X a subsidiary of Y" — resolve a user-spoken NAME to the canonical/official identifiers other tools require as input. Use FIRST whenever you have a name but need an ID. SUPPORTED TYPES: "company" (cross-source identity spine: 10-digit CIK + ticker + company_name from SEC EDGAR, legal-entity LEI from GLEIF with parent/ultimate-parent/children ownership when the LEI resolves, and security FIGI from OpenFIGI — by exact ticker map when a ticker is implied, and otherwise by name search, so NON-EQUITY instruments that never have a ticker (municipal and corporate bonds, notes, authority debt) DO resolve here; when a name matches more than one instrument it asserts nothing and returns figi_candidates to pick from, which is the correct answer to an issuer name that does not identify a single bond; every identifier is labelled with the source that established it, and an identifier that could NOT be resolved is stated explicitly under unresolved rather than omitted — accepts ticker, CIK, ISIN, or company name as input; an ISIN like "CH0038863350" resolves to the LEGAL ENTITY that issued the security via the GLEIF ISIN-to-LEI mapping, covering non-US issuers EDGAR cannot reach), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/concept/{rxcui} citation; accepts brand or generic name). LEI/FIGI enrichment degrades gracefully — if GLEIF or OpenFIGI is unavailable, the EDGAR identifiers still return. Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type: "company" or "drug".
valueYesFor company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., "ozempic", "metformin"). Pass the ENTITY NAME ONLY — for a bond that is the ISSUER exactly as printed ("NEW YORK ST DORM AUTH"), never the question's full noun phrase ("NEW YORK ST DORM AUTH revenue bonds"): the FIGI lookup matches instrument names, so trailing security-class words match nothing.

Schema Changelog

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

  1. Changed1 schema field changed
    • changedInput schema / properties / value / description
      Previous value: -"For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., \"ozempic\", \"metformin\")."New value: +"For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., \"ozempic\", \"metformin\"). Pass the ENTITY NAME ONLY — for a bond that is the ISSUER exactly as printed (\"NEW YORK ST DORM AUTH\"), never the question's full noun phrase (\"NEW YORK ST DORM AUTH revenue bonds\"): the FIGI lookup matches instrument names, so trailing security-class words match nothing."
  2. Changed3 schema fields changed
    • changedInput schema / properties / type / description
      Previous value: -"Entity type. v1 supports \"company\"."New value: +"Entity type: \"company\" or \"drug\"."
    • changedInput schema / properties / type / enum
      Previous value: -[
-  "company"
-]New value: +[
+  "company",
+  "drug"
+]
    • changedInput schema / properties / value / description
      Previous value: -"Ticker, CIK, or company name (e.g., \"AAPL\", \"0000320193\", \"Apple\")."New value: +"For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., \"ozempic\", \"metformin\")."
  3. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds significant behavioral detail: it cascades through multiple endpoints, degrades gracefully if GLEIF/OpenFIGI are unavailable, explicitly reports unresolved identifiers under 'unresolved', asserts nothing on ambiguity, and labels identifiers by source. No contradictions 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.

Conciseness4/5

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

The description is long and packed with details, but every sentence adds value—covering supported types, edge cases, and behavioral notes. It is front-loaded with the core purpose and usage instruction ('Use FIRST...') and then elaborates. While not succinct, it is not redundant, and the length is justified by the tool's complexity. A minor deduction for verbosity, but it remains appropriately structured.

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

Completeness5/5

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

Given the tool's complexity (two types, multiple sources, edge cases) and the lack of an output schema, the description is exceptionally complete. It explains outputs for company (CIK, ticker, LEI, FIGI, unresolved) and drug (RxCUI, ingredient, brand), covers degradation and ambiguity, and even clarifies how bonds resolve. The description fully prepares an agent to call the tool correctly and interpret results.

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

Parameters5/5

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

Schema coverage is 100% and each parameter has a description, but the description adds substantial semantics beyond the schema. It explains accepted formats for 'value' (ticker, CIK, ISIN, name), the importance of passing the entity name only (with a bond example), and the difference between company and drug types. It also clarifies the 'type' enum with examples ('drug: brand or generic name'), exceeding the schema's brief descriptions.

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 states a specific verb (resolve) and resource (entity names to canonical identifiers), with a clear list of example queries ('What's the ticker for…', 'find the CIK for…'). It distinguishes itself from siblings by emphasizing it is the first step when a name needs an ID, and it explicitly covers types (company, drug) and explains how it resolves bonds via FIGI. This makes the purpose unambiguous and distinct from other tools.

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

Usage Guidelines5/5

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

The description explicitly says 'Use FIRST whenever you have a name but need an ID,' providing a strong directive for when to invoke it. It also explains nuanced cases (e.g., when an ISIN is provided, it resolves to the legal entity; when a name matches multiple instruments, it returns figi_candidates). While it doesn't list alternatives, the 'Use FIRST' phrasing and the coverage of specific lookups give clear usage context.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially the multiple 'ask_pipeworx' variants and several Polymarket utilities. The server mixes a few timezone tools with a large collection of unrelated data lookup and analysis tools, making it hard for an agent to distinguish which tool to use for a given task.

Naming Consistency2/5

While all tool names use snake_case, the verbs are highly inconsistent (e.g., 'ask_pipeworx', 'convert_time', 'discover_tools', 'validate_claim'). There is no clear pattern or predictable naming convention across the set.

Tool Count2/5

The server name 'timezone' suggests a narrow domain, but it contains 35 tools, the vast majority of which are unrelated to timezones. This is far too many for the implied scope, and the server seems to be a dumping ground for various services.

Completeness1/5

For a timezone server, only 4 tools (convert_time, get_time_by_ip, get_time_by_timezone, list_timezones) are relevant. Critical timezone functionality like time zone conversions with arbitrary offsets, DST handling, or time zone by coordinates is missing. The remaining tools are completely unrelated to the server's stated purpose.

Resources