Skip to main content
Glama

Rxnorm

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

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive, and the description adds substantial behavioral context: ambiguous matches return figi_candidates instead of asserting, identifiers are source-labelled, unresolved identifiers are listed, LEI/FIGI enrichment degrades gracefully, and each call cascades through multiple endpoints. This goes far beyond annotation coverage and is highly relevant to calling the tool correctly.

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 front-loaded with trigger examples and the direct 'Use FIRST' instruction, but it is a long, dense block with a massive parenthetical and multiple clauses. Most sentences carry unique information, so nothing is fluff, but the readability suffers from the run-on structure. It earns credit for density but loses a point for lack of conciseness.

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?

There is no output schema, so the description carries the burden of explaining return content. It does so thoroughly: for companies it lists the delivered identifiers (CIK, ticker, company_name, LEI, FIGI, ownership), and for drugs it lists RxCUI, ingredient, brand, and citation. It also covers failure modes (ambiguity, source unavailability, unresolved identifiers), making the behavior fully comprehensible to an agent.

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 description coverage is 100%, so the baseline is 3, but the tool description enriches both parameters. The 'type' parameter gains meaning through detailed explanations of what a company lookup returns versus a drug lookup. The 'value' parameter is augmented with input formats (ticker, CIK, ISIN, brand/generic name) and the critical caveat about passing the entity name only, not the full noun phrase. This surpasses 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 and resource: 'resolve a user-spoken NAME to the canonical/official identifiers.' It opens with concrete trigger examples and positions itself as the 'FIRST' step when a name is present but an ID is needed, clearly distinguishing it from downstream tools like entity_profile or direct RxNorm lookups. The scope (names to identifiers, including CIK, LEI, FIGI, RxCUI) is explicit and unambiguous.

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 explicitly says 'Use FIRST whenever you have a name but need an ID,' giving a clear when-to-use rule. It enumerates supported types and accepted input formats. However, it does not name an alternative tool for when not to use it (e.g., if the agent already has an ID), so it stops short of the full when/when-not/alternatives structure.

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

All Rxnorm 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

A3.6/5.0
Disambiguation2/5

Several tools blur together: ask_pipeworx_beta currently duplicates ask_pipeworx exactly, ask_pipeworx/ask_pipeworx_grounded/deep_research/validate_claim all route natural-language questions to data sources, and the prediction-market tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, bet_research) have fuzzy boundaries. The detailed descriptions help, but an agent can easily misselect among them.

Naming Consistency3/5

All names are lowercase snake_case and the rxnorm_, polymarket_, and pipeworx_ prefixes create readable groupings, but the set mixes imperative verb-object names (validate_claim, list_subscriptions), noun-phrase names (entity_profile, recent_alerts), and bare verbs (remember, forget). It is readable but not a predictable uniform naming convention.

Tool Count2/5

35 tools is in the too-many band for a coherent server, and the Rxnorm identity makes it worse: only 4 tools are actually RxNorm-specific while 31 are unrelated Pipeworx, prediction-market, memory, and utility tools. A focused RxNorm server would need a fraction of this surface.

Completeness3/5

The four rxnorm_* tools plus resolve_entity cover the main RxNorm lookup flow (search, properties, related, NDC), so the core is not broken. But the set lacks a reverse NDC-to-concept lookup and the 31 non-RxNorm tools do not complete any single coherent domain, leaving notable gaps relative to the server's stated purpose.

Resources