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Understanding Document Embeddings, Knowledge Graphs, and Vector Representations MCP tools

Production-ready MCP servers that extend AI capabilities through file access, database connections, APIs, and contextual services.

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47,284 tools. Last updated 2025-12-28 16:36

  • ollama_embed

    Ollama MCP Server

    Generate numerical vector embeddings from text inputs to enable semantic search, similarity analysis, and machine learning applications.
    AGPL 3.0

  • semantic_search

    memento-mcp

    Search your knowledge graph memory using semantic vector embeddings to find entities similar to your query, with options for hybrid search, similarity thresholds, and entity type filtering.
    MIT License

  • create_embeddings

    Grok MCP Server

    Generate embeddings for text using the Grok API, specifying model, input, encoding format, and dimensions for accurate vector representations.
    MIT License

  • manageVector

    Cursor10x MCP

    Manage vector embeddings for Cursor10x MCP by performing store, search, update, and delete operations to enhance AI memory retention and recall.
    MIT License

  • get_entity_embedding

    memento-mcp

    Retrieve vector embeddings for specific entities from the memento-mcp knowledge graph memory to enable semantic search and relation management.
    MIT License

  • semantic_search

    Moatless MCP Server

    Search code using natural language queries with vector embeddings. Filter results by code chunk type and retrieve relevant matches efficiently.

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