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"Finding tasks for large language model agents" matching MCP servers:

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    Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on developer productivity with: * Multi-Project Support: Isolate memories into separate "brains" (Context Cores). * GraphRAG: Automatically builds a knowledge graph from your context. * Sub-200ms Search: Blazing fast Hybrid & Semantic
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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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    1,091
    Apache 2.0
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    Enables semantic search and interaction with Fuel Network documentation and Sway Language resources within AI-powered development environments. It provides high-quality technical context using a local vector database to assist with smart contract development and FuelVM queries.
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    An 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.
    240
    Apache 2.0
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    A 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
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    A 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.
    6
    MIT
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    Enables Claude Desktop to search private documents using Azure AI Search and perform web searches with Bing, providing AI-enhanced results with source citations through Azure AI Agent Service or direct Azure AI Search integration.
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    A smart code retrieval tool based on Model Context Protocol that provides efficient and accurate code repository search capabilities for large language models.
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  • F
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    A 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.
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    A production-grade semantic search server for food recipes — built for AI agents using the Model Context Protocol (MCP). Search across 50,000+ recipes with hybrid dense + sparse retrieval and cross-encoder reranking.
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    MIT
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    A Model Context Protocol server that allows Large Language Models to interact with Astra DB databases, providing tools for managing collections and records through natural language commands.
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    Apache 2.0
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    Enables AI agents to manage and search data in Redis using natural language. Supports hashes, lists, sets, sorted sets, streams, JSON, and vector search.
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    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 production-grade Model Context Protocol server for PostgreSQL. Lets AI agents safely inspect, query, operate, and tune a Postgres database — over 100 tools spanning catalog introspection, query intelligence, natural-language SQL, structural diffs, hybrid search, graph queries, data movement, live ops, and more.
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    MIT
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    A lightweight server implementation of the Model Context Protocol that connects Memgraph database with LLMs, allowing users to interact with graph databases through natural language.
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    A Model Context Protocol server for indexing and searching local document collections with hybrid BM25+vector search, optimized for Korean and English, supporting DOCX, PDF, audio, and more.
    MIT