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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 -

Matching MCP tools:

Matching MCP servers:

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    A Model Context Protocol (MCP) server that optimizes token usage by caching data during language model interactions, compatible with any language model and MCP client.
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    The official Redis MCP Server is a natural language interface designed for agentic applications to efficiently manage and search data in Redis.
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    Enables AI assistants to maintain persistent conversations and context between sessions through automated saving and global installation across projects. Provides zero-configuration memory persistence with automatic conversation history preservation.
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    A Model Context Protocol server that reduces token consumption by efficiently caching data between language model interactions, automatically storing and retrieving information to minimize redundant token usage.
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    Persistent memory and pattern learning for AI coding assistants via MCP.
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    The Redis Cloud API MCP Server provides an MCP Server for Redis Cloud's API, allowing you to manage your Redis Cloud resources using natural language.
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    Provides access to Redis databases. This server enables LLMs to interact with Redis key-value stores through a set of standardized tools.
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    Enables AI assistants to perform comprehensive Redis database operations including managing strings, hashes, lists, sets, sorted sets, TTL management, and data backup/restore. Supports secure connections and provides batch operations for efficient Redis interaction through natural language.
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    Enables users to perform Redis database operations using the Model Context Protocol (MCP) tools, allowing for efficient data management through commands like setting, getting, and scanning hash fields.
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    A server that provides Claude with Redis database access and operations through a set of tools for basic operations, lists, hashes, sets, and pub/sub functionality.
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    Provides tools to create, update, delete, and search catalog items through the Turbify Store Catalog API.
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    A persistent AI conversation system that uses OpenAI's API integrated with Upstash Redis for session storage, allowing users to maintain context across multiple conversations with support for tool integration via MCP architecture.
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    MIT License
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    All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...
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    A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.
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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 comprehensive memory system for Cursor using the Model Context Protocol (MCP) that provides persistent context awareness across sessions by storing conversation history, project milestones, code snippets, and enabling semantic search.
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    Provides Claude with real-time system monitoring capabilities, including CPU, memory, disk, network, battery, and internet speed metrics.
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    • Apple
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    Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and ownership of your data. Integrates directly with Obsidan.md
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    Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.
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    A lightweight, stateless MCP server utilizing Puppeteer for web searches, returning structured JSON results, easily integratable with other MCP-enabled systems.
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    A comprehensive Model Context Protocol server that enables AI assistants to interact with and manage Windows systems, providing capabilities for file system operations, process management, system information retrieval, registry operations, service management, network diagnostics, and performance monitoring.
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    A high-performance, persistent memory system for the Model Context Protocol (MCP) providing vector search capabilities and efficient knowledge storage using libSQL as the backing store.
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    A Model Context Protocol server that allows users to store, retrieve, update, and delete memories using SQLite storage.
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    A custom Memory MCP Server that acts as a cache for Infrastructure-as-Code information, allowing users to store, summarize, and manage notes with a custom URI scheme and simple resource handling.
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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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    A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.
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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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    A server implementing the Model Context Protocol that provides filesystem operations (read/write, directory management, file movement) through a standardized interface with security controls for allowed directories.
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    Enables AI agents to store, retrieve, and manage contextual knowledge across sessions using semantic search with PostgreSQL and vector embeddings. Supports memory relationships, clustering, multi-agent isolation, and intelligent caching for persistent conversational context.
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    A Model Context Protocol server that enables Claude to persistently store, search, and manage text memories with tags in a local JSON file.
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