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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.
    1
    MIT
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    A server that provides access to Baidu Cloud Vector Database functionality through the Model Context Protocol, enabling LLM applications to perform vector searches and database operations via natural language.
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    Apache 2.0
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    A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.
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    Enables semantic search and analysis of customer support tickets. Provides tools to search tickets, analyze the dataset, and retrieve individual tickets using natural language.
    3
    MIT
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    An MCP server that enables RAG-powered AI chat integration for websites by crawling content, building local vector stores, and generating embeddable chat widgets. It simplifies the setup of local chat servers with support for various LLM and embedding providers.
    5
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    MIT
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    ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.
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    1,080
    Apache 2.0
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    Python MCP server for vector search using Qdrant vector database and Ollama embeddings, with advanced query techniques like query expansion, HyDE, and reranking.
    2
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    MIT
  • F
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    Integrates R2R (Retrieval-Augmented Generation) with Claude Desktop, enabling semantic search across knowledge bases and RAG-based question answering with support for vector, graph, web, and document search.
    2
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    XMemo is a secure, user-owned memory substrate and context engine for AI agents, CLIs, IDEs, and LLM workspaces. Exposed over Streamable HTTP MCP, it empowers agents with cross-session memory, task continuity, and personalized context. Key Features: * Personalized Context: Stores and recalls developer preferences, project guidelines, and coding patterns via semantic vector search. * Agent Daily Me
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    MIT
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    Self-hosted mem0 MCP server for Claude Code that adds durable async ingestion, document support, and reranking, enabling persistent memory management with Qdrant, Neo4j, and Ollama.
    15
    1
    MIT