Skip to main content
Glama

Openaire

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. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses real behavioral traits: it cascades through multiple lookup endpoints, degrades gracefully when GLEIF/OpenFIGI are unavailable, returns figi_candidates instead of asserting ambiguous matches, and explicitly lists unresolved identifiers.

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 long, but nearly every sentence carries functional guidance—examples, supported types, failure modes, and lookup behavior. It is front-loaded with a clear purpose statement, though some parentheticals are lengthy and could be tightened.

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 two-parameter lookup tool with no output schema, the description is remarkably complete: it specifies identifiers returned per type, source provenance, unresolved behavior, ambiguity handling, ISIN-to-LEI mapping, and graceful degradation. An agent has enough context to select and invoke this tool correctly.

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 the description adds substantial param semantics: detailed value examples for both type enum values, clarification that only the entity name should be passed, and a specific warning that trailing security-class words break FIGI matching. This goes well beyond the schema 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 and resource: resolving user-spoken entity names to canonical/official identifiers. It explicitly enumerates supported entity types, acceptable input forms, and returns, making it easy to distinguish from siblings like entity_profile or compare_entities.

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 opens with concrete user-phrase examples and a direct instruction: 'Use FIRST whenever you have a name but need an ID.' It also explains when ambiguity occurs, what is returned in that case, and how enrichment degrades, providing clear contextual selection guidance.

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

All Openaire toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation2/5

Several tools have heavily overlapping or explicitly duplicate purposes: ask_pipeworx_beta is described as currently identical to ask_pipeworx, while ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim all route natural-language queries to similar lookup pipelines. The Polymarket tools also blur together (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk), and scan_competitor_ai_presence is just a wrapper around ai_visibility_check.

Naming Consistency3/5

There are readable verb-led names like search_publications, get_project, resolve_entity, and validate_claim, but the set mixes conventions with noun-phrase names like entity_profile, recent_alerts, polymarket_edges, and pipeworx_trending. The lack of a single verb_noun pattern makes the surface feel inconsistent, though each family is internally recognizable.

Tool Count2/5

At 37 tools, this is well beyond the 25+ threshold where an agent starts paying significant selection and context cost. The broad domain could justify some breadth, but many tools are meta-wrappers or near-duplicates (ask_pipeworx_beta, compare_entities, entity_profile, deep_research) that inflate the count.

Completeness4/5

Within its main subdomains, the surface is fairly complete: OpenAIRE search has matching get_project/get_research_product retrieval, memory has remember/recall/forget, subscriptions have subscribe/unsubscribe/list/recent_alerts, and there are discovery/onboarding helpers like suggest_questions and discover_tools. Minor gaps exist (e.g., no direct generic Polymarket market quote tool, no memory update besides overwrite), but no major workflow is a dead end.

Resources