Skip to main content
Glama

Census Trade

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

A4.8/5.0
Behavior5/5

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

The annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior, but the description adds substantial context: parallel fan-out across nine sources, soft-failure of the USPTO feed after May 2025, 'an empty section is a real no data, not a bug,' and 'resolved:false with an explicit notes line' for private companies. This goes well beyond the structured annotations and sets accurate expectations for both success and failure modes.

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, especially the single run-on sentence listing all return sections, but almost every clause carries operational information. It is front-loaded with the core purpose and routing preference, and the detailed caveats are all useful given the tool's complexity and lack of an output schema. It could be better structured, but it contains no filler.

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 the full burden of explaining return values, and it does so thoroughly: cik, company_name, resolved_from/to, recent_filings with URIs, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used, and sources_failed. It also explains edge cases like private companies, expected empty sections, and source soft-failures, so an agent has enough context to invoke the tool and interpret its response correctly.

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%, so the schema documents both parameters well. The description adds genuine value by clarifying that `type` accepts 'company' or 'ticker' interchangeably, that `value` can be a ticker, CIK, or name regardless of `type`, and that names resolve via SEC EDGAR's company-name match. This normalization semantics is the kind of nuance an agent needs beyond the 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 states a specific action and resource: 'full cross-source profile of a US public company in ONE parallel call,' reinforced by concrete user phrasings like 'Tell me about X' and 'company profile for Microsoft.' It distinguishes itself from sibling tools by saying it fans out across SEC, XBRL, patents, contracts, FDA, hiring, news, and GLEIF, so an agent can clearly tell entity_profile apart from single-source lookups like resolve_entity or compare_entities.

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 gives an explicit routing rule: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also specifies accepted value shapes (ticker, zero-padded CIK, or company name) and the expected behavior for private companies (resolved:false with notes), leaving no ambiguity about when and how to invoke the tool.

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

All Census Trade 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

A3.8/5.0
Disambiguation2/5

There is substantial overlap among the question-routing tools: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and ask_pipeworx_grounded, deep_research, and validate_claim all funnel natural-language queries into similar source lookups. ai_visibility_check and scan_competitor_ai_presence also cover nearly the same capability, making tool selection genuinely ambiguous.

Naming Consistency3/5

All names are snake_case and many follow a verb_noun pattern (census_exports, list_subscriptions, validate_claim), but the convention drifts with noun-first names like entity_profile, pipeworx_trending, and recent_alerts, and bare verbs like remember, recall, forget, and subscribe. It is readable but not a tight, predictable pattern.

Tool Count2/5

35 tools is too many for a server named 'Census Trade' when only 4 of them actually relate to Census trade data. The remaining 31 form an unrelated general-purpose data, prediction-market, memory, and subscription toolkit, making the surface feel bloated and badly scoped relative to the server's apparent purpose.

Completeness3/5

The Census trade core covers exports, imports, trade balance, and monthly trends, which handles the central queries, but there is no HS-code catalog, country metadata, or state/port-level breakdown, leaving notable gaps for a trade-data domain. If judged as the broad Pipeworx gateway it appears to actually be, coverage is richer, but that contradicts the server name and weakens overall coherence.

Resources