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Glama

Coinmarketcap

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

A4.8/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint), the description reveals the fan-out behavior, fallback logic (GDELT→GNews), USPTO soft-fail, and structured return format, adding significant behavioral context.

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 concise and front-loaded with example queries. It efficiently covers sources, parameters, return format, and alternative tool without redundancy.

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?

Without an output schema, the description details the return structure (changes[] grouped by source, total_changes, citation URIs). All necessary context for proper invocation is present.

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%, but the description adds value by explaining 'since' accepts ISO dates or relative shorthand ('7d', '30d', '1y') with a recommendation ('30d' or '1m'). It also clarifies 'value' accepts ticker or CIK.

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, fanning out to SEC EDGAR, GDELT→GNews, and USPTO. It explicitly distinguishes from the sibling tool entity_profile, which covers static profiles.

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 gives explicit usage examples ('What's new with X', 'latest on Y') and directs to use entity_profile for static profiles, providing clear guidance on when not to use this tool.

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

A3.7/5.0
Disambiguation3/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route queries to structured data sources, differing mainly in depth and hallucination resistance. Similarly, entity_profile, compare_entities, recent_changes, and validate_claim all provide company information, leading to potential selection ambiguity for an agent.

Naming Consistency2/5

Tool names mix conventions: snake_case (ai_visibility_check, ask_pipeworx), camelCase (discover_tools, entity_profile), and inconsistent verb placement (scan_competitor_ai_presence vs ask_pipeworx). There is no consistent verb_noun pattern across the set, making the naming chaotic.

Tool Count3/5

The server has 37 tools, which is slightly high but acceptable given the broad scope (CoinMarketCap data, Pipeworx gateway, Polymarket integration, memory utilities). However, a significant portion are meta-tools that route to many sub-tools, inflating the count. The server named 'Coinmarketcap' contains many non-CMC tools, which feels mismatched.

Completeness4/5

The server covers the core CoinMarketCap functionality (listings, quotes, categories) and provides extensive external integrations via Pipeworx (SEC, FDA, FRED, etc.) and Polymarket (edges, arbitrage). Minor gaps exist (e.g., no historical price tool for CMC, no direct tool for obtaining CMC API keys), but the overall surface is comprehensive for its intended use cases.

Resources