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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

A3.8/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful behavioral context: parallel fan-out across sources, `sources_used`/`sources_failed` semantics, 'an empty section is a real "no data", not a bug', and name resolution via SEC EDGAR. It stops short of 5 because the garbled patents/fundamentals segment muddies exactly what data behavior is guaranteed.

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 description is a single dense run-on paragraph with repeated and corrupted fragments such as 'LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted by? Actually it says...' and 'patentsView patent filings); patentsView patents'. It is not front-loaded or well-structured; key return information is buried amid noise and editorial-sounding interruptions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description must explain return values; it attempts to list cik, company_name, recent_filings, fundamentals, and sources_used/sources_failed, and it covers edge cases like private companies. However, the corrupted mid-section leaves the patents and fundamentals details unclear, and limits/pagination beyond 'up to 5' filings are not specified.

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%, so the description has little burden to explain parameters. The description does reinforce that 'type' accepts company/ticker interchangeably and that 'value' can be a ticker, CIK, or name, but this duplicates the schema's own parameter documentation without adding new semantic meaning.

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 states the core purpose: 'full cross-source profile of a US public company in ONE parallel call' and gives example queries like 'company profile for Microsoft'. It also differentiates from single-pack lookups by saying 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups'. However, the excessive corruption and run-on wording in later sections obscure the full scope of what the profile includes.

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?

The description explicitly tells the agent when to use this tool: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also provides clear input guidance (ticker, CIK, or company name) and explains the private-company fallback with 'resolved:false'. This is an explicit decision rule with a named alternative.

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

A3.9/5.0
Disambiguation2/5

Several tools are near-identical: ask_pipeworx and ask_pipeworx_beta are explicitly the same right now, and the three ask_pipeworx variants plus deep_research all route the same underlying catalog. The six polymarket_* tools also have heavily overlapping purposes, requiring deep reading to choose correctly. Most other tools are distinguishable, but these clusters create real misselection risk.

Naming Consistency3/5

The set is uniformly snake_case and mostly descriptive, with consistent micro-families like remember/recall/forget and polymarket_*. However, there is no single convention across the server: verb_noun names (ask_pipeworx, list_subscriptions) mix with noun-first names (entity_profile, bet_research, nearest_color), and the Pipeworx brand is used as both prefix and suffix. Readable but inconsistent.

Tool Count2/5

At 34 tools, the surface is far larger than a typical well-scoped server, and the count is especially unjustified for a server named 'Color' where only three tools relate to that name. The breadth stems from bolting a full data-research platform, prediction-market suite, memory store, and subscription system onto what appears to be a simple utility. Too heavy.

Completeness4/5

For the dominant Pipeworx research domain, the set is unusually thorough: query, grounded verification, deep research, entity resolution, comparisons, claim validation, change feeds, subscriptions, alerts, memory, and discovery are all present. Minor gaps exist (e.g., no direct account management tool, and color coverage only includes convert/contrast/nearest with no palette generation), but these are workaround-able. Completeness is strong for the real domain, if mismatched with the server name.