Skip to main content
Glama

Entity Profile

entity_profile
Read-onlyIdempotent

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when value was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. sources_used / sources_failed say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit notes line, not a bare failure. type accepts "company" or "ticker" interchangeably — both take the same value shapes above.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes"company" or "ticker" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon.
valueYesTicker (e.g., "AAPL"), zero-padded CIK (e.g., "0000320193"), or company name (e.g., "Moderna") — names resolve via SEC EDGAR company-name match.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • changedInput schema / properties / type / description
      Previous value: -"Entity type. Only \"company\" supported today; person/place coming soon."New value: +"\"company\" or \"ticker\" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon."
    • changedInput schema / properties / type / enum
      Previous value: -[
      -  "company"
      -]New value: +[
      +  "company",
      +  "ticker"
      +]
    • changedInput schema / properties / value / description
      Previous value: -"Ticker (e.g., \"AAPL\") or zero-padded CIK (e.g., \"0000320193\"). Names not supported — use resolve_entity first if you only have a name."New value: +"Ticker (e.g., \"AAPL\"), zero-padded CIK (e.g., \"0000320193\"), or company name (e.g., \"Moderna\") — names resolve via SEC EDGAR company-name match."
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond readOnly/idempotent/openWorld hints, the description discloses meaningful behavior: it fans out across multiple sources, reports sources_used/sources_failed, clarifies that an empty section is real 'no data' not a bug, notes FDA product absence is expected for non-biologics, and explains private-company fallback behavior. 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.

Conciseness3/5

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

The description is front-loaded and information-dense, but it is a long single paragraph with redundant examples and schema repetition. It would be easier for an agent to parse with paragraph breaks or bullets; not every repeated example earns its place.

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 complex tool with no output schema, the description is unusually complete: it enumerates sources, return fields (cik, company_name, recent_filings URIs, fundamentals), source success/failure reporting, and expected no-data behavior. It gives an agent enough context to invoke it correctly without seeing a detailed output schema.

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 coverage is 100% and the schema already documents ticker/CIK/name formats and type interchangeability. The description adds extra operational meaning about edge cases (private company returns resolved:false with notes, empty sections are expected), but much of its parameter discussion repeats schema text.

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 clearly identifies the tool as a full cross-source profile of a US public company, backed by many trigger examples ('Tell me about X', 'company profile for Microsoft'). It does not explicitly name or contrast sibling tools like deep_research, compare_entities, or resolve_entity, 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 Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly instructs 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view', which is a direct when-to-use and alternative directive. It also specifies acceptable inputs and what happens for private companies, making selection unambiguous.

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

A3.9/5.0
Disambiguation3/5

Most tools have distinct, well-scoped purposes, but several question-answering/research tools sit close together: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim can all be selected for factual questions. The descriptions are detailed enough to reduce ambiguity, but ask_pipeworx_beta is currently identical to ask_pipeworx, and discovery helpers like discover_tools, suggest_questions, and pipeworx_trending also overlap somewhat.

Naming Consistency4/5

Names are uniformly snake_case and mostly follow a verb_noun pattern such as build_url, list_subscriptions, resolve_entity, and validate_claim. The polymarket_* and pipeworx_* prefixes form a readable convention, though a few names like pipeworx_feedback and polymarket_arbitrage are noun-phrases rather than verb-first actions.

Tool Count2/5

34 tools is well past the 25+ threshold where even a broad platform starts to feel bloated. The set mixes data research, prediction-market tooling, URL utilities, memory, subscriptions, feedback, and npm scanning, which would be more coherently split across focused servers.

Completeness3/5

The core research workflows are thoroughly covered: routing, grounded answers, deep research, entity resolution, comparisons, claim validation, discovery, alerts, and memory all exist. However, the URL utility and dependency-scanning side domains feel tacked on and incomplete, and there is no dedicated tool to fetch an arbitrary pipeworx:// citation record even though such URIs are returned throughout.