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Glama

Open Corporates

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

The description adds rich behavioral context beyond annotations: fan-out to multiple sources, fallback logic, USPTO soft-fail due to API sunset, return format (grouped changes, count, citation URIs). This fully informs the agent of the tool's behavior and limitations.

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 a single dense paragraph but remains front-loaded with examples and key capabilities. Every sentence adds value. A minor improvement would be to break into sections, but it is still efficient and clear.

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?

Given the tool's complexity (multiple data sources, fallback, parameter nuances) and no output schema, the description is remarkably complete. It covers return format, source behavior, parameter syntax, and even notes an API sunset. It also links to a sibling for an alternative use case.

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 description builds on that. It clarifies 'since' with examples and typical usage, explains that 'value' accepts ticker or CIK, and notes that only 'company' is supported for 'type'. This adds meaningful detail without redundancy.

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 starts with concrete query examples and clearly states it returns a change feed for a company over a window. It lists specific sources (SEC EDGAR, GDELT→GNews, USPTO) and explicitly distinguishes the sibling tool entity_profile, so the purpose is both specific and differentiated.

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 provides an explicit alternative ('Use entity_profile instead when you want the static profile') and explains fallback behavior (GDELT→GNews). It also suggests typical window values ('30d' or '1m'). While not exhaustive about when-not-to-use, it offers clear guidance.

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

All Open Corporates toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Multiple tools route the same underlying Pipeworx catalog (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, discover_tools, suggest_questions), and six prediction-market tools overlap heavily. Detailed descriptions help, but an agent could easily pick the wrong entry point, especially since ask_pipeworx_beta is currently identical to ask_pipeworx.

Naming Consistency3/5

All names are lowercase snake_case, giving a baseline of consistency, but the pattern is mixed: verb-first names like search_companies and validate_claim sit alongside noun-phrase names like entity_profile, polymarket_edges, and recent_changes. The polymarket_* family is predictable, but overall the naming does not follow one convention.

Tool Count2/5

34 tools is well over the threshold for a coherent surface, and the majority have nothing to do with the server's stated Open Corporates purpose—only get_company, search_companies, and search_officers belong to that domain. The rest are Pipeworx research, Polymarket, memory, subscription, and miscellaneous utilities bolted on.

Completeness2/5

The actual OpenCorporates portion is thin and has composition problems: search_companies does not describe returning a company number, yet get_company requires one, and search_companies references a gleif search_lei tool that is not present in this server. The broader Pipeworx side is comprehensive, but for the server's named purpose the surface can dead-end and is incomplete.

Resources