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    maintenance
    A long-horizon memory architecture for AI agents, providing a scalable, graph-based memory with causal typing and an MCP interface.
    4
    2
    Business Source 1.1
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    Provides semantic search capabilities by connecting Claude Desktop to a Cloudflare Workers backend powered by Vectorize. It enables natural language querying of knowledge bases using vector similarity and edge-based embedding generation.
    2
    MIT
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    quality
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    MCP server for Qdrant vector database with local BERT embeddings. Enables semantic search and vector storage operations through natural language.
    MIT
  • A
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    A
    maintenance
    MCP server for Milvus vector database enabling vector search, text search, and hybrid search operations.
    Apache 2.0
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    Enables AI assistants to interact with MariaDB databases through standard SQL operations and advanced vector/embedding-based search. Supports database management, schema inspection, and semantic document storage and retrieval with multiple embedding providers.
    MIT
  • F
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    quality
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    maintenance
    The MCP Server for Weaviate facilitates integration with Weaviate using a customizable Python-based server, enabling interaction with Weaviate databases and OpenAI APIs via configurable URL and API keys.
    163
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  • F
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    Provides local-first memory storage and retrieval with automatic embedding, vector search, and knowledge graph capabilities. Enables agents to store memories locally and retrieve relevant context through hybrid search with optional Neo4j graph traversal.
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  • A
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    quality
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    maintenance
    Universal MCP server for readonly-first access to Oracle, SQL Server, PostgreSQL, MySQL/MariaDB, SQLite, MongoDB, and Qdrant vector search.
    116 npm
    1
    MIT
  • A
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    quality
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    maintenance
    Enables semantic search across browser bookmarks from Chrome, Firefox, Edge, Opera, and other browsers using natural language queries. Extracts and indexes bookmark content and metadata into a vector database for intelligent retrieval.
    1
    Apache 2.0
  • F
    license
    Not graded
    quality
    D
    maintenance
    A smart code retrieval tool based on Model Context Protocol that provides efficient and accurate code repository search capabilities for large language models.
    34
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  • A
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    maintenance
    Provides AI assistants with long-term semantic memory capabilities through local vector-based storage. Enables storing, recalling, and managing information across sessions with complete privacy using ChromaDB, with no data ever leaving your machine.
    3
    9
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Enables AI agents to interact with an embedded graph database (GrafeoDB) via the Model Context Protocol, providing tools for graph CRUD, GQL queries, full-text and vector search, and graph algorithms.
    23
    4
    Apache 2.0
  • A
    license
    A
    quality
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    maintenance
    A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.
    3
    1
    MIT
  • F
    license
    A
    quality
    D
    maintenance
    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.
    3
    3
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