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Open-Source MCP servers

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

9,443 servers. Last updated -

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    A long-term memory storage system for LLMs that helps them remember context across multiple sessions using semantic search with embeddings to provide relevant historical information from past interactions and development decisions.
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    Implements long-term memory capabilities for AI assistants using PostgreSQL with pgvector for efficient vector similarity search, enabling semantic retrieval of stored information.
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    Enables AI assistants to store and retrieve long-term memories using PostgreSQL with vector similarity search. Supports semantic memory operations, tagging, and real-time updates for persistent learning across conversations.
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    Provides long-term memory capabilities for Claude through persistent storage and full-text search of context across conversations. Enables storing, searching, and managing memories organized by categories like facts, preferences, projects, and goals.
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    The Cursor10x Memory System creates a persistent memory layer for AI assistants (specifically Claude), enabling them to retain and recall short-term, long-term and episodic memory on autonomously.
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    Enables neural memory sequence learning with a memory-augmented model for improved code understanding and generation, featuring state management, novelty detection, and model persistence.
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    Provides persistent memory and semantic code understanding for AI assistants using MongoDB Atlas Vector Search. Enables intelligent code search, memory management, and pattern detection across codebases with complete semantic context preservation.
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    A robust server for managing long-term agent memory using Mem0, providing efficient storage and retrieval of agent memories with a lightweight Python-based implementation.
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    Provides AI agents with persistent long-term memory capabilities using semantic search. Enables storing, retrieving, and searching memories through three core tools integrated with Mem0 and vector storage.
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    An MCP server that provides persistent memory capabilities for Claude, offering tiered memory architecture with semantic search, memory consolidation, and integration with the Claude desktop application.
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    Memory Bank Server provides a set of tools and resources for AI assistants to interact with Memory Banks. Memory Banks are structured repositories of information that help maintain context and track progress across multiple sessions.
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    An MCP server that extends AI agents' context window by providing tools to store, retrieve, and search memories, allowing agents to maintain history and context across long interactions.
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    A customized MCP memory server that enables creation and management of a knowledge graph with features like custom memory paths and timestamping for capturing interactions via language models.
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    Model Context Protocol (MCP) memory server built with Azure Functions and TypeScript, providing persistent knowledge graph storage for your preferred MCP client. Inspired by and forked from @modelcontextprotocol/server-memory
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    Cline MCP integration that allows users to save, search, and format memories with semantic understanding, providing tools to store and retrieve information using vector embeddings for meaning-based search.
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    A knowledge-graph-based memory system for AI agents that enables persistent information storage between conversations.
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    A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.
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    Persistent development memory server that automatically captures and organizes development context, code changes, and user interactions across projects.
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    Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.
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    Manages knowledge graph data synchronized with GitHub repositories, enabling remote storage and collaboration of memory entities, relationships, and observations.
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    Provides knowledge graph functionality for managing entities, relations, and observations in memory with strict validation rules to maintain data consistency.
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    Provides persistent graph memory with automatic disk storage for building knowledge graphs, storing entity relationships, and maintaining context across sessions.
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    A sophisticated MCP server providing advanced memory capabilities with RAG, hallucination detection, and enterprise-grade AI infrastructure for intelligent agent ecosystems.
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    A high-performance MCP server utilizing libSQL for persistent memory and vector search capabilities, enabling efficient entity management and semantic knowledge storage.
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    Provides a structured documentation system for context preservation in AI assistant environments, helping users create and manage memory banks for their projects.
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    This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.
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    Enhances Claude AI with persistent memory storage for Infrastructure-as-Code components, supporting version tracking and relationship mapping for Terraform and Ansible resources.
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    Enables AI assistants to maintain persistent project context across sessions by storing and retrieving structured information in markdown files organized in a memory bank directory.
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    A memory server for Claude that stores and retrieves knowledge graph data in DuckDB, enhancing performance and query capabilities for conversations with persistent user information.
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    A Python-based server that implements the Model Context Protocol to interface with Claude Desktop as an MCP client, supporting interaction through efficient memory management.
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    An advanced MCP server providing RAG-enabled memory through a knowledge graph with vector search capabilities, enabling intelligent information storage, semantic retrieval, and document processing.
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