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"Techniques for Document Compression and Chunking" matching MCP servers:

  • A
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    A
    quality
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    maintenance
    An MCP server that exposes documents.js's document conversion, .odb, metadata, and font tooling as MCP tools, enabling agents to convert, inspect, and edit a wide range of document formats over stdio.
    18
    7,693
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    A local document evidence layer for MCP clients that ingests documents (PDF, Office, images) with optional OCR, indexes them in SQLite FTS, and provides retrieval tools with source coordinates.
    7
    MIT
  • F
    license
    A
    quality
    C
    maintenance
    A local AI document assistant MCP server that enables listing, reading, and editing documents via tools, resources, and prompts, allowing LLMs to manage document workflows through natural language.
    3
  • A
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    quality
    D
    maintenance
    Enables AI agents to search, deep-read, and build knowledge bases from Markdown, PDF, DOCX, and PPTX documents via MCP tools for retrieval, document navigation, and ingestion.
    70
    616
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    Converts PDFs, Office files, spreadsheets, emails, audio, and more to Markdown locally, enabling AI assistants to read and process them without cloud upload.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables AI agents to efficiently manage and update component documentation with precise partial updates, saving up to 75% tokens compared to full rewrites.
    ISC
  • A
    license
    Not graded
    quality
    D
    maintenance
    Local document intelligence for AI agents — extract text, detect tables, read metadata, analyze structure, search keywords, and detect language from PDF and DOCX files. No cloud API required, no API key needed.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables real-time indexing and semantic search of local documents (PDF, Word, text, Markdown, RTF) using vector embeddings and local LLMs. Monitors folders for changes and provides natural language search capabilities through Claude Desktop integration.
    22
    MIT
  • F
    license
    Not graded
    quality
    C
    maintenance
    Enables reading and searching documents in allowlisted folders via LiteLLM and MCP tools, using COM for Office files to support IRM-protected content.
  • A
    license
    A
    quality
    B
    maintenance
    Indexes local documents (PDF, Word, Markdown, text) into a SQLite database for AI agents to search and retrieve bounded, source-located passages. Runs fully locally with optional OCR, preserving privacy.
    5
    MIT