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syaryn
by syaryn

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    • A
      license
      B
      quality
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      Enables AI agents to search any local folder through a private SQLite FTS5 index that extracts text from PDFs, Office documents, plain text, code and zip listings, returning ranked matches instead of slow ls/grep scans. It also supports metadata and glob listing, paged retrieval of already-extracted text, duplicate detection, and incremental background re-indexing with secrets and caches excluded by default.
      8
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables AI agents to search a local folder of Markdown, AsciiDoc, and text files through a SQLite FTS5 keyword index, returning the most relevant sections with file paths, line ranges, and heading breadcrumbs instead of grepping through a repo. It also exposes tools to list indexed documents and refresh the index incrementally, all offline with no dependencies, network calls, or embeddings.
      3
      MIT
    • A
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      Not graded
      quality
      A
      maintenance
      Enables agents to run full-text search inside Word, PowerPoint, Excel, PDF, and plain-text files by extracting their contents into a single local SQLite FTS5 index. Exposes tools to search documents with ranked highlighted snippets and human-readable locators, list indexed files, and incrementally build or refresh the index.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI assistants to run incremental SQLite FTS5 full-text search over explicitly configured local workspace roots, covering Markdown, code, PDF, DOCX, XLSX, CSV and HTML with BM25 ranking, Chinese bigrams, and phrase, prefix, path, type and date filters. Exposes search, safe root-confined reads with line/page/sheet locations, recent-file listing, and reindexing as MCP tools so assistants can locate and quote source content without network or account access.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables fast, low-token code search for AI coding agents via a local BM25 engine built on SQLite FTS5, with support for camelCase, snake_case, and Japanese text. Provides a stateless MCP stdio server and a Hermes adapter for multi-agent environments.
      1
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Provides local semantic search over files using embeddings, enabling directory indexing and natural language queries without external services.
      50 PyPI
      MIT

    TDQS

    A3.8/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool has a distinct purpose: delete, stats, index directory, list files, search, update single file, watch directory. No overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case, e.g., delete_index, get_index_stats, search_documents.

    Tool Count5/5

    7 tools cover the core operations for a file indexing server without being excessive or insufficient.

    Completeness5/5

    The tool set includes full lifecycle management: initial indexing, incremental updates, watching, listing, searching, stats, and bulk deletion. No obvious gaps.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues