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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

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses substantial behavioral nuance: it fans out across multiple sources in parallel, soft-fails on the USPTO PatentsView sunset, returns empty fda_products for non-biologic companies (explicitly 'expected, not a failure'), and reports sources_used/sources_failed so empty sections are interpretable.

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 and dense, front-loaded with query examples and the key usage directive. It is a single wall of text rather than scannable bullets, but nearly every sentence carries a necessary caveat or output detail for a multi-source tool, so the length is largely justified.

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 carries full responsibility for explaining return shape and edge cases. It covers all major output sections (filings, fundamentals, contracts, FDA products, hiring, news, LEI), resolver behavior, failure semantics, and accepted input forms. Very little an agent needs to invoke this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%: both `type` and `value` are already well-described in the input schema, including the interchangeability of 'company' and 'ticker'. The description adds minor context like zero-padded CIK format and SEC EDGAR name resolution, but mostly restates what the schema already conveys. Baseline 3 is appropriate.

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 query examples and a crisp definition: 'full cross-source profile of a US public company in ONE parallel call.' It names the exact resource (entity) and the specific verb/profile operation, and distinguishes itself from single-pack SEC/XBRL/news lookups, so an agent can identify it without reading the schema.

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 tells the agent when to use this tool ('when the user asks for a holistic view') and even provides a preference rule: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups.' It also covers edge-case usage behavior, such as private companies returning resolved:false with a notes line rather than a bare failure.

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

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TDQS

A3.5/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical, and the five polymarket_* tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) all target prediction-market opportunities. The memory tools (remember/recall/forget) are distinct, as are subscriptions, but the routing and Polymarket clusters create real misselection risk.

Naming Consistency3/5

All names are snake_case, but the pattern is mixed: some are verb_noun (ask_pipeworx, compare_entities, discover_tools, resolve_entity), some are noun_verb or adjective_noun (bet_research, entity_profile, pipeworx_trending, recent_changes), and some are bare nouns/verbs (lookup, query, recall, relatedness). The 'polymarket_*' and 'ask_pipeworx*' families are consistent internally, but the overall set lacks a uniform verb-first convention.

Tool Count2/5

With 34 tools, the server is heavily over-scoped for a server named 'Conceptnet' — the vast majority of tools belong to a separate Pipeworx data-access product, not a semantic-network API. While each tool has a use, the count feels bloated and the server name misrepresents the actual surface.

Completeness4/5

The ConceptNet portion is complete (lookup, query, relatedness cover graph traversal). The Pipeworx portion is also fairly complete: universal router, grounded mode, deep research, entity profiles, comparisons, claim validation, subscription lifecycle, memory, and feedback. Minor gaps exist (e.g., no direct SEC filing fetch without going through ask_pipeworx), but the meta-tools mostly fill them.