Skip to main content
Glama

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.

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the read-only, idempotent annotations, the description discloses meaningful runtime behavior: internal cascading across multiple lookup endpoints, graceful degradation when GLEIF or OpenFIGI is unavailable, support for non-equity instruments without tickers, and explicit `unresolved` reporting rather than silent omission. This gives an agent accurate expectations for fallback and edge cases.

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 dense and front-loaded with the trigger and supported types, and most content earns its place. However, the company-type block is a very long parenthetical with run-on structure, making it harder to parse than the information density justifies.

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?

For a tool with no output schema, the description covers what an agent needs to know: per-type return values, source coverage, ISIN resolution to legal entities, degraded enrichment behavior, and explicit unresolved handling. It is complete for the tool's complexity and integration role.

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?

Although the schema already documents both parameters, the description adds critical meaning: accepted `value` formats include ticker, CIK, ISIN, or name; drug names can be brand or generic; and for bonds the value must be the issuer exactly as printed, not the full noun phrase including security-class words. This is substantial semantic guidance beyond the schema.

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

Purpose4/5

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

The description names a specific operation — 'resolve a user-spoken NAME to the canonical/official identifiers' — and gives concrete use phrasings and supported types. It does not explicitly distinguish itself from sibling tools like entity_profile or compare_entities, so it falls just short of full sibling differentiation.

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 gives an explicit trigger: 'Use FIRST whenever you have a name but need an ID,' and illustrates the kinds of questions that should route here. It does not name alternative tools or state when not to use this tool, so exclusion guidance is missing.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation3/5

Most tools have distinct purposes, but several clusters overlap: ask_pipeworx_beta is currently identical to ask_pipeworx, polymarket_arbitrage and polymarket_edges both surface arbitrage opportunities, and validate_claim overlaps with ask_pipeworx_grounded. Descriptions mitigate some confusion, but selection errors are still likely.

Naming Consistency4/5

Names are overwhelmingly lowercase snake_case and descriptive, such as nist_control_family, polymarket_fill_risk, and list_subscriptions. Minor deviations exist with single-word memory verbs like remember/recall/forget and the ask_pipeworx_* variants, but the overall pattern is predictable and readable.

Tool Count2/5

34 tools is well above the comfortable range and includes many tools unrelated to the server's NIST Standards name, such as Polymarket betting, npm dependency scanning, AI visibility checks, and llms.txt generation. The set feels like a broad general-purpose data platform rather than a scoped NIST reference server.

Completeness3/5

For the NIST domain, the three control tools provide id lookup, family listing, and keyword search, but there is no catalog overview or family enumeration, and no comparison, revision, or export capability. The other 31 tools do not fill those gaps, so the NIST surface is functional but not fully complete for compliance workflows.