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RITIKA-SHARMAA

RAG-MCP

by RITIKA-SHARMAA
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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

    A4.4/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: search returns ranked passages, get_chunk retrieves a specific chunk, get_document retrieves a full document, and list_documents provides an overview. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    All tool names follow the same verb_noun pattern with lowercase and underscores: search_documents, get_chunk, get_document, list_documents. The convention is perfectly consistent.

    Tool Count5/5

    Four tools form a tight, well-scoped set for a RAG server. Each tool earns its place by covering the essential retrieval workflow without redundancy or bloat.

    Completeness5/5

    The tool surface covers the full retrieval lifecycle: discover what's indexed (list_documents), search the corpus (search_documents), read a specific passage (get_chunk), and read the full source (get_document). No obvious gaps exist for the stated purpose.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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