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licenseNot graded
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maintenanceEnables 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
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"Techniques for Document Compression and Chunking" matching MCP servers:
- AlicenseNot gradedqualityDmaintenanceEnables 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.22MIT
- FlicenseNot gradedqualityCmaintenanceMCP server enabling Claude Desktop to answer questions from local Word and PDF documents by searching a vector index built from their contents.
- AlicenseNot gradedqualityDmaintenanceA vector search system that enables semantic retrieval of document chunks using MongoDB Atlas Vector Search and Voyage AI embeddings, allowing users to search documents by meaning rather than just keywords.2MIT
- AlicenseNot gradedqualityDmaintenanceA deterministic MCP server for document processing and retrieval that enables AI agents to process, chunk, and vector-search documents without an LLM.MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to search and retrieve relevant document content from existing embeddings stored in Supabase vector database. Provides semantic search capabilities to find document chunks based on similarity to query text without generating new embeddings.MIT
- FlicenseNot gradedqualityDmaintenanceEnables 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.
- AlicenseNot gradedqualityDmaintenanceA Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.Apache 2.0
- AlicenseNot gradedqualityBmaintenanceThis MCP server provides semantic document search and retrieval, enabling AI assistants to search documents, search categories, and retrieve category hierarchies using the Model Context Protocol.2MIT
- AlicenseNot gradedqualityCmaintenanceAn integration server implementing the Model Context Protocol that enables LLM applications to interact with Milvus vector database functionality, allowing vector search, collection management, and data operations through natural language.240Apache 2.0
- FlicenseNot gradedqualityCmaintenanceAn MCP server that enables Claude Desktop or Claude Code to ingest and search local documents using vector embeddings, returning relevant chunks as tool results for the model to reason over.
- FlicenseNot gradedqualityDmaintenanceTransforms CSV and Excel data into Markdown-formatted vector embeddings stored in a local ChromaDB instance for semantic search. It enables MCP clients to retrieve relevant tabular data through single-row, batch, or free-text queries.
- FlicenseNot gradedqualityCmaintenanceEnables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.
- FlicenseNot gradedqualityNot gradedmaintenanceA local Retrieval-Augmented Generation system that enables users to ingest markdown files into a FAISS-powered vector knowledge base for semantic search. It provides tools for document indexing and context retrieval to support informed LLM queries without external dependencies.
- FlicenseNot gradedqualityDmaintenanceEnables AI systems to remember interactions, understand document context through semantic search, and intelligently route requests with persistent memory and quality-scored content synthesis.
- AlicenseNot gradedqualityCmaintenanceEnables document ingestion, semantic search, and retrieval-augmented generation via MCP tools and REST API, using vector embeddings and intelligent chunking.MIT
- AlicenseNot gradedqualityDmaintenanceA local-first Graph-RAG system combining ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q&A over Obsidian vaults, supporting MCP clients like Claude Desktop, Cursor, and Raycast.MIT
- AlicenseNot gradedqualityDmaintenanceA server implementation that allows secure communication between MCP clients and privateGPT, enabling users to chat with privateGPT using knowledge bases and manage sources, groups, and users through a standardized Model Context Protocol.6MIT
- AlicenseNot gradedqualityCmaintenanceAn MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.10MIT
- FlicenseNot gradedqualityCmaintenanceEnables document Q&A and knowledge retrieval through hybrid semantic and keyword search, with tools for document ingestion, chunking, summarization, PII redaction, and RAGAS-based evaluation.