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Datamuse

Server Details

Datamuse MCP — word-finding engine (keyless).

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Status
Unhealthy
Last Tested
Transport
Streamable HTTP
URL
Repository
pipeworx-io/mcp-datamuse
GitHub Stars
0

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool update
    • Changeddeep_research1 field changed
      • changedInput schema / properties / depth / description
        Previous value: -"How many facets to research in parallel: quick=3 (single hop), standard=5 (default; adds a gap-recovery hop that re-angles unanswered facets + a contradictions[] scan across findings), thorough=8 (paid; adds a full iterative hop that chases leads + recovers gaps, plus the contradictions[] scan)."New value: +"How many facets to research in parallel: quick=3 (single hop), standard=3 (default; adds a gap-recovery hop that re-angles unanswered facets + a contradictions[] scan across findings), thorough=6 (paid; adds a full iterative hop that chases leads + recovers gaps, plus the contradictions[] scan)."

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TDQS

A3.9/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all provide similar data querying. Multiple Polymarket tools also overlap. This makes it difficult for an agent to select the correct tool.

Naming Consistency3/5

Most names use snake_case, but patterns vary: some start with verbs (ask_, compare_, generate_, etc.), others with nouns (bet_research, entity_profile, recent_alerts). This mix reduces predictability.

Tool Count2/5

With 31 tools, the server feels bloated. Many tools are meta-tools or variants (e.g., three ask_pipeworx versions). The count is high for the apparent scope, which includes data querying, prediction markets, memory, and subscriptions.

Completeness4/5

The server covers a vast range of data sources and operations (company financials, prediction markets, memory, subscriptions, etc.). It is comprehensive for its intended data querying and analysis domain, with few obvious gaps (e.g., no non-company entity profiles).