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    Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.
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    1
    MIT
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    A fully modular RAG system with MCP protocol integration, enabling hybrid retrieval, multimodal support, and dual-mode transport for connecting to AI assistants like GitHub Copilot and Claude Desktop.
    Last updated
    5
    1
    MIT
  • F
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    Intelligent knowledge base system that enables users to process documents in 25+ formats, perform semantic search and Q\&A through vector retrieval. Supports multiple AI models including OpenAI and DouBao with local processing capabilities.
    Last updated
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    5
  • A
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    Provides local Retrieval-Augmented Generation (RAG) capabilities using Ollama for embeddings and ChromaDB for vector storage. It enables users to ingest and perform semantic searches across PDF, Markdown, and TXT documents within MCP-compatible clients.
    Last updated
    4
    37
    1
    MIT
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    Enables semantic search and contextual conversations with your Calibre ebook library using vector-based RAG technology. Supports project-based organization, multi-format book processing, and OCR capabilities for enhanced content extraction and retrieval.
    Last updated
    7
    2
  • F
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    MCP server for searching, browsing, and analyzing decompiled Minecraft source code locally. Supports symbol lookup, text search, reference lookup, and lightweight RAG.
    Last updated
    11
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    Combines a knowledge graph with RAG (Retrieval-Augmented Generation) capabilities for semantic code indexing and search. Enables creating entity relationships, managing observations, and performing semantic searches across indexed codebases.
    Last updated
    13
  • A
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    A Model Context Protocol (MCP) server that provides powerful RAG (Retrieval-Augmented Generation) capabilities for PDF documents. This server uses ChromaDB for vector storage, sentence-transformers for embeddings, and semantic chunking for intelligent text segmentation.
    Last updated
    MIT
  • A
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    A powerful Model Context Protocol server that creates intelligent graph representations of your codebase with comprehensive semantic analysis capabilities, supporting 11 languages and 26 MCP methods.
    Last updated
    54
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    MIT
  • A
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    A server that integrates Retrieval-Augmented Generation (RAG) with the Model Control Protocol (MCP) to provide web search capabilities and document analysis for AI assistants.
    Last updated
    4
    Apache 2.0
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    An MCP server that indexes documents and serves relevant context to LLMs via Retrieval Augmented Generation (RAG).
    Last updated
    37
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    MIT