Skip to main content
Glama

Arcgis Washingtoncomn

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.

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, openWorld), the description discloses rich behavior: cross-source resolution cascade, ambiguous-name handling returning figi_candidates, explicit unresolved identifiers, and graceful degradation when GLEIF/OpenFIGI are unavailable. This genuinely helps an agent anticipate 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 long but every sentence carries operational value—examples, supported types, failure modes, and degradation behavior. It is front-loaded with practical usage guidance. Slight redundancy in the identifier enumeration could be tightened, but complexity justifies the length.

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?

With no output schema, the description adequately covers return behavior: company identifiers, drug identifiers, figi_candidates, unresolved list, and source labelling. It could be more explicit about the exact output shape for company resolution, but it provides enough for an agent to set expectations.

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 adds substantial meaning beyond it: the value parameter's 'ENTITY NAME ONLY' rule, the bond issuer exact-name example, the warning about trailing security-class words, and the semantics of type=company vs type=drug. This far exceeds the schema's terse 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 opens with concrete user phrasing examples and states the precise function: resolving a user-spoken NAME to the canonical/official identifiers other tools require. It clearly distinguishes itself from siblings like entity_profile or compare_entities by positioning this as the first-step ID lookup tool.

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?

It explicitly says 'Use FIRST whenever you have a name but need an ID,' which is a clear when-to-use directive. It also gives per-type guidance (company vs drug) and warns against passing full noun phrases. It does not name sibling alternatives or spell out when-not-to-use, but the condition is strongly implied.

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

All Arcgis Washingtoncomn 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

A3.8/5.0
Disambiguation3/5

The ArcGIS tools (query_layer, layer_info, search_datasets) are clearly distinct, but the Pipeworx family has heavy overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and discover_tools can all appear as plausible entry points for a similar data lookup task. The memory and subscription tools are well separated, but the router-style tools create real ambiguity.

Naming Consistency4/5

Almost all tools use lowercase snake_case names with a verb-first pattern (ask_pipeworx, query_layer, subscribe, remember) or clear noun descriptors (entity_profile, layer_info, polymarket_edges). A few names are more cryptic (recall, forget, resolve_entity) but they still follow the same style. No mixed camelCase or inconsistent separators.

Tool Count2/5

34 tools is well beyond what the apparent ArcGIS Washington County purpose needs; only three tools actually concern GIS data. The rest are a broad Pipeworx research suite, memory, subscriptions, feedback, and AI-visibility probes. This makes the surface feel like two or three unrelated servers grafted together rather than one scoped package.

Completeness3/5

For the ArcGIS slice, you can discover, inspect, and query layers, but there is no write or create capability, no field-wise editing, no map/feature export, and no feature-level CRUD. The Pipeworx data side is more comprehensive, but the overall server confuses its purpose. The mixed-domain coverage leaves the GIS part only a thin slice of the offered features.

Resources