Skip to main content
Glama

Delaware DMV

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

A4.6/5.0
Behavior5/5

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

Annotations already mark the tool read-only/idempotent/non-destructive, and the description adds non-obvious behavior: ambiguous names yield `figi_candidates`, LEI/FIGI enrichment degrades gracefully when upstream sources fail, and each call cascades through multiple endpoints. No contradiction 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.

Conciseness2/5

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

The opening examples and use-first directive are good, but the body is one dense run-on paragraph with malformed fragments such as 'more than one instrument it asserts nothing' and inerleaved ISIN/CIK/FIGI guidance. The useful content would benefit from bullets or clear sectioning; as written it is hard to parse.

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?

For a tool with no output schema, it covers returned identifiers, ambiguity behavior, ownership enrichment, degradation, and the main input caveats. It is not quite complete because the output shape/error convention is never stated cleanly and the malformed passages make some claims unreliable, but an agent has most of what it needs.

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%, but the description goes beyond it: it explains that `value` for a bond must be the issuer name exactly as printed, that trailing security-class words break the FIGI match, and which input forms each type accepts. This materially improves on the schema alone.

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 names a specific operation — resolving a user-spoken name into canonical/official identifiers — and backs it with query paraphrases and the two supported types. It also distinguishes coverage (non-equity instruments resolve here; ISINs route to resolve_ciks_or_issuer), so an agent knows what this tool is for.

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?

It explicitly directs use 'FIRST whenever you have a name but need an ID,' provides an ISIN alternative, notes there is no sibling for non-equity instruments, and gives value-format guidance for bonds and drugs. This is stronger than most tool descriptions.

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

All Delaware DMV 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 are effectively duplicates or near-duplicates: ask_pipeworx and ask_pipeworx_beta are described as currently identical, ai_visibility_check and scan_competitor_ai_presence overlap heavily, and the polymarket_arbitrage/polymarket_edges/polymarket_fill_risk cluster has fuzzy boundaries. Even within the DMV subset, de_dmv_ev_adoption and de_dmv_vehicle_registrations both answer overlapping EV-count questions.

Naming Consistency2/5

The de_dmv_* tools follow one snake_case pattern, but the rest of the set mixes bare nouns, brand-prefixed verbs, and generic names (entity_profile, remember, generate_llms_txt, ask_pipeworx_beta). There is no consistent verb_noun or domain-prefix convention across the 36 tools.

Tool Count2/5

36 tools is over the threshold where a tool set becomes hard to navigate, and most of them have nothing to do with a Delaware DMV server. Only five tools are DMV-related; the rest are a general-purpose Pipeworx data, memory, and prediction-market toolkit, which makes the set feel bloated and mis-scoped.

Completeness2/5

For a server named Delaware DMV, the surface is missing core DMV capabilities like driver licenses, vehicle titling, registration renewals, appointments, or fee lookups. The five de_dmv_* tools cover only EV adoption, rebates, charger rebates, crash stats, and registration counts, leaving obvious domain gaps.

Resources