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PyContextify

by tbrandenburg
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Python

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    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clear, distinct purpose: status for system info, reset_index for clearing, index_filebase for adding content, discover for listing tags, and search for querying. There is no overlap or ambiguity between these operations.

    Naming Consistency4/5

    Most tool names are concise verbs (status, discover, search) while two use verb_noun (reset_index, index_filebase). The pattern is mostly consistent and readable, but not perfectly uniform in structure.

    Tool Count5/5

    The server has 5 tools, which is well-scoped for an indexing and semantic search system. Each tool serves a necessary function without redundancy or bloat.

    Completeness4/5

    The core lifecycle is covered: add content (index_filebase), query (search), discover tags (discover), reset (reset_index), and monitor (status). A minor gap is the absence of a targeted delete/remove operation for specific content, but the reset option provides a workaround.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources