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document-index-mcp

by ekelly95

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      The open retrieval layer for AI agents. Index your entire project — code, docs, legal, research, data — and serve surgical context via MCP. FTS5 full-text search, optional semantic search (FastEmbed/ONNX), 10 built-in parsers, incremental auto-sync.
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    TDQS

    A4.6/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a distinct role: search_document finds snippets, get_chunk_context retrieves full text, get_document_outline provides structure, ingest_document adds content, and delete_document removes it. There is no overlap in purpose; the descriptions clearly differentiate when to use each.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (ingest_document, delete_document, search_document, get_chunk_context, get_document_outline). The prefix 'get_' is used consistently for retrieval operations, and the other verbs are clear and action-oriented.

    Tool Count5/5

    Five tools is well-scoped for a document indexing and retrieval server. Each tool is necessary and there are no redundant or superfluous entries. This is within the ideal range for a focused MCP server.

    Completeness5/5

    The tool surface covers the full document lifecycle: ingest (create), read via search/context/outline, update via re-ingestion (explicitly stated), and delete. It also includes library listing and ingestion status polling, so there are no obvious dead ends or missing capabilities for the stated purpose.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues