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Qdrant RAG Build

by avaazquezz
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Python
Hybrid

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    • Chalee MCP RAG

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    • RAG Factory

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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

    A3.7/5.0

    Scored across 33 tools

    Disambiguation4/5

    Most tools have clearly distinct roles, and the descriptions carefully separate collection lifecycle, ingestion, retrieval, and setup wizard operations. The search family is the main risk area: search, search_hybrid, search_rerank, search_multi_query, and get_context all overlap semantically, though their descriptions are precise enough to disambiguate with careful reading.

    Naming Consistency3/5

    The server uses readable lowercase snake_case throughout, but there is no single naming convention: object-first names like collection_list and document_list coexist with verb-first names like get_context and ingest_text, plus bare nouns such as health, stats, and job_status. Subfamilies are internally consistent, but the overall pattern is mixed.

    Tool Count2/5

    33 tools for a RAG build server is well past the 25+ 'too many' threshold. The tool count is inflated by an 8-tool search/retrieval family plus a setup wizard, profile system, and collection management layer, making the surface feel heavier than the core RAG job really requires.

    Completeness4/5

    The server covers the RAG lifecycle well: collection creation, ingestion from multiple sources, document management, snapshots, search, context assembly, setup wizardry, profiles, and health/stats. Minor gaps like no alias_delete or payload_index_delete are awkward but can be worked around without dead-ending an agent.

    Maintenance

    ActivityMaintained
    ResponsivenessSyncing

    Resources