Skip to main content
Glama

Press Release

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. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint; the description adds details about fanning out to multiple sources, fallback behavior, and output structure. No contradictions.

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 well-structured, front-loading purpose and examples, then detailing sources, parameters, and return value. It is relatively long but every sentence adds value; minor redundancy in example queries.

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

Completeness4/5

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

Given no output schema, the description explains the return structure (changes[] grouped, total_changes, URIs). It covers limitations (USPTO soft-fail) and fallback logic, though error handling is not fully detailed.

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 description coverage is 100%; the description adds examples for the 'since' parameter (e.g., '7d', '30d') and clarifies the 'value' parameter accepts ticker or CIK, but does not significantly extend 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 clearly states the tool provides a change feed for a company in a time window, using example queries to illustrate use cases. It distinguishes itself from sibling entity_profile by noting when to use the alternative.

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 guidance on when to use entity_profile instead, and explains the fallback mechanism for GDELT→GNews. It does not cover all sibling tools but provides good context for the primary alternative.

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

All Press Release 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

Several tools have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants (beta is explicitly identical to stable), and the six Polymarket tools heavily overlap in finding edges and arbitrage. discover_tools and suggest_questions also serve similar discovery purposes, causing likely misselection.

Naming Consistency4/5

All names are lowercase snake_case with mostly verb-first or clear prefixes (ask_, polymarket_, pipeworx_, recent_). Minor deviations like `press_release_generate` (noun-verb) and `entity_profile` (noun-noun) break the otherwise consistent pattern, but the naming remains readable and predictable.

Tool Count2/5

At 32 tools, the count exceeds the 25+ threshold and feels bloated for a server whose stated purpose is 'Press Release.' The toolset sprawls across unrelated domains (data lookups, prediction markets, memory, AI visibility, npm scanning), making the size more of a liability than a well-scoped strength.

Completeness2/5

For a server named 'Press Release,' the surface is severely incomplete: only one satirical press release generator exists, with no drafting, editing, publishing, or distribution tools. The other 31 tools serve unrelated domains, so an agent expecting press-release lifecycle support hits significant dead ends.

Resources