Skip to main content
Glama

Congress

by io.github.pipeworx-io

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. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description then adds substantial behavioral context: it fans out across many sources, soft-fails on USPTO PatentsView, treats empty sections as real 'no data', returns resolved:false for private companies with an explicit notes line, and explains how name resolution and type interchangeability behave. 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.

Conciseness4/5

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

The description is long but appropriately so for a multi-source, high-complexity tool, and it is front-loaded with examples and the core 'ONE parallel call' promise. It is organized with clear backticked output keys and scannable clauses, though some input-shape details are repeated from the schema, keeping it from being maximally concise.

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?

Even though there is no output schema, the description thoroughly explains return sections: cik, resolved_from/resolved_to, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used, and sources_failed. It also covers edge cases like empty sections being real no-data, private companies returning resolved:false, and soft-fail behavior, leaving an agent well-equipped to call and interpret the result.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful extra semantics: type values are 'interchangeable', value can be a ticker, zero-padded CIK, or company name, and names resolve via SEC EDGAR company-name match. This goes beyond the schema's already-good parameter 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 intents ('Tell me about X', 'research Acme', 'brief me on Tesla') and immediately states the deliverable: 'full cross-source profile of a US public company in ONE parallel call.' It distinguishes itself from single-pack SEC/XBRL/news lookups by commanding 'ALWAYS PREFER' when a holistic view is requested, giving the tool a clear identity among its siblings.

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?

The description gives explicit triggers ('Tell me about X' / 'research Acme' / etc.) and a strong routing rule: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It does not explicitly name sibling tools such as compare_entities or resolve_entity as alternatives or exclusions, so the routing guidance is strong but not fully exhaustive.

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

All Congress 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

A3.9/5.0
Disambiguation2/5

Multiple tools occupy the same functional space: ask_pipeworx, ask_pipeworx_beta, ask_ipeworx_grounded, and deep_research all answer questions; disover_tools, suggest_questions, and pipeworx_trending all serve discovery; and five polymarket_* tools plus bet_research overlap heavily on prediction-market opportunity detection. The descriptions are detailed, but the boundaries are subtle enough that an agent can easily pick the wrong tool.

Naming Consistency4/5

The set is uniformly lowercase snake_case and uses recognizable prefixes such as ask_pipeworx, polymarket_, pipeworx_, and get_, which makes the naming fairly predictable. It is not a strict verb_noun convention — some names are noun phrases like entity_profile or ai_visility_check — but the overall style is consistent.

Tool Count2/5

With 36 tools, the surface is far heavier than the 'Congress' name suggests: only five tools are actually about congressional data, while the rest are general research, memory, subscription, and meta utilities. Many of these overlap, so the count feels bloated rather than well-scoped.

Completeness3/5

For Congress-specific work, the core needs are covered: search bills, get bill details, list members, and retrieve recent votes. However, deeper legislative operations like member voting records, committee actions, and amendments are missing, and the surrounding Pipeworx tools do nothing to close that gap. As a general data-research platform it is broad, but its actual 'Congress' identity feels incompletely realized.

Resources