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

  • A
    license
    Not graded
    quality
    C
    maintenance
    Provides AI agents with comprehensive document parsing capabilities including PDF text extraction, OCR, HTML-to-markdown conversion, table extraction, and summarization, optimized for agent workflows.
    101
    MIT
  • 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
  • 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
  • A
    license
    Not graded
    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
    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
  • A
    license
    Not graded
    quality
    D
    maintenance
    An MCP server that uses the Docling toolkit to convert various document formats, including PDFs, Office files, images, and audio, into clean Markdown for AI processing. It supports multiple processing pipelines like VLM and ASR with intelligent auto-detection and job queue management.
    2
    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.
  • F
    license
    Not graded
    quality
    D
    maintenance
    Efficiently delivers project documentation to AI agents like Claude on-demand, optimizing token usage by loading context only when needed. Supports document retrieval, listing, and keyword search with security features.
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables natural language search and analysis of uploaded PDF, CSV, and Excel documents using retrieval-augmented generation and MCP tools, providing contextual answers to user queries.
    MIT
  • F
    license
    Not graded
    quality
    C
    maintenance
    A local MCP server that answers natural language questions over a collection of research PDFs, using semantic retrieval and Gemini for grounded answers with citations.
  • A
    license
    A
    quality
    C
    maintenance
    Verifiable document intelligence for AI agents. Extract text, tables, and structured data from PDFs and URLs. Summarize, answer questions, check claims, and translate — all with cited evidence. Store tamper-evident evidence bundles with cryptographic signatures and on-chain attestation via Base L2. Cross-document semantic search and Q&A across named collections. Pay per call with USDC
    22
    15
    1
    MIT
  • A
    license
    B
    quality
    A
    maintenance
    MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.
    24
    6
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.
    1
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    Enables semantic search and question-answering over uploaded documents using vector embeddings and Google AI. Supports document organization with tags, section-aware queries, and hierarchical markdown structure preservation.
  • A
    license
    A
    quality
    A
    maintenance
    An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.
    2
    18,221
    MIT