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

A4.9/5.0
Behavior5/5

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

The description discloses far more than the annotations: it explains parallel fan-out across multiple sources, soft-fails for the USPTO patents API sunset, the expected empty FDA section for non-biologic companies, the semantics of sources_used/sources_failed, and the resolved:false private-company behavior. This is exemplary behavioral transparency.

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 it is front-loaded with trigger examples and packed with necessary operational details. Every major behavioral and return-semantic point earns its place, though some redundancy around source enumeration 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?

With no output schema, the description must carry return-value documentation, and it does: it lists all returned sections (cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI) plus sources_used/failed. It also covers error/edge cases, making it complete for a tool of this complexity.

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 already 100%, but the description adds meaningful detail beyond the schema: type values are interchangeable, value can be ticker/CIK/name, names resolve via SEC EDGAR match, and person/place support is coming soon. This materially improves parameter understanding beyond the raw schema.

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 verb-resource pair ('full cross-source profile of a US public company') and includes many concrete trigger examples. It clearly differentiates itself from chained single-pack lookups and is unambiguous about being a holistic entity profile tool.

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?

Explicitly instructs 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also specifies accepted input forms, how names resolve, and what happens for private companies, giving the agent strong selection and invocation guidance.

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

B3.3/5.0
Disambiguation2/5

ask_pipeworx and ask_pipeworx_beta are currently described as functionally identical, which is a direct ambiguity, and ai_visibility_check/scan_competitor_ai_presence plus the polymarket_* tools create several overlapping boundaries. The long descriptions help, but an agent still has to read deep into each one to avoid selecting the wrong tool.

Naming Consistency3/5

Most tools use readable lowercase snake_case verb_noun names like discover_tools, resolve_entity, and validate_claim, but the set also includes bare nouns like gene and tissues, verb-only memory tools like remember/recall/forget, and noun-phrase names like entity_profile, recent_changes, and pipeworx_trending. The style is not chaotic, but no single convention is sustained.

Tool Count2/5

36 tools exceeds the 25+ threshold and the surface is heavily padded with overlapping meta-tools, near-duplicate routers, and unrelated clusters such as Polymarket arbitrage, AI-visibility checks, and GTEx expression queries. For a server named Gtex, most of these tools are outside the apparent domain, making the count feel overgrown rather than well-scoped.

Completeness2/5

The GTEx-specific subset has only five tools and lacks obvious endpoints like multi-issue eQTLs, isoform expression, or sample-level querying, while the remaining 31 tools belong to unrelated Pipeworx, Polymarket, memory, and subscription domains. There is no coherent single purpose against which the surface can be considered complete, so agents will often hit dead ends or spend calls figuring out what the server is actually for.