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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.

9,512 servers. Last updated -

Matching MCP tools:

Matching MCP servers:

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    A Model Context Protocol server that allows AI assistants to communicate with the ChatGPT desktop app on macOS, enabling users to send prompts to ChatGPT from any MCP-compatible assistant.
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    Enables Claude Desktop and VS Code Claude CLI to interact with ChatGPT on Windows systems through the MCP protocol. Provides seamless integration allowing users to leverage ChatGPT functionality within their Claude workflow with tools for sending messages, managing conversations, and accessing ChatGPT responses.
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    MCP ChatGPT Responses connects Claude to ChatGPT through two essential tools: standard queries for AI-to-AI conversations and web-enabled requests for current information. It uses OpenAI's Responses API to maintain conversation state automatically.
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    Allows tracking of parcel deliveries across various carriers using the 17track.net API, with automatic or manual carrier detection.
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    Enables users to manage tasks through a simple JSON file interface. Provides basic task management functionality by reading and writing to a configurable tasks.json file.
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    MIT License

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    A Model Context Protocol server that enables Docker container management through natural language interactions using a custom GPT interface.
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    A task management system for AI-driven development with Claude, designed to work seamlessly with Cursor AI and other code editors via MCP.
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    Enables intelligent task management with status tracking, dependency resolution, and automatic next task discovery based on preconditions and priorities. Supports hierarchical task structures with subtasks and flexible JSON-based configuration.
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    A Model Context Protocol server providing comprehensive task management capabilities with support for project organization, task tracking, and automatic PRD parsing into actionable items.
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    Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.
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    A Model Context Protocol implementation that provides a standardized interface for task management, supporting both STDIO mode for CLI/AI applications and HTTP+SSE mode for browser-based clients.
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    Enables AI assistants to manage tasks through YAML-based storage with subtask suggestions, status updates, and Mermaid Gantt chart generation. Supports hierarchical task structures with attributes like dependencies, milestones, and parallel execution.
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    A bridge between MCP Host applications and mem0 cloud service, specialized for project management with capabilities to store, retrieve, and search project information within a structured format.
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    MCP Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.
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    An MCP server for Task Trellis that provides tools for AI coding agents to manage tasks, currently featuring a simple hello_world demonstration tool.
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    This MCP server enables agents to manage complex tasks by providing tools for registration, complexity assessment, breakdown into subtasks, and status tracking throughout the task lifecycle.
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    An MCP server that integrates with AI editors like Cursor to maximize agentic capabilities while solving context window limitations, providing a Svelte UI for task planning and implementation tracking.
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    A knowledge-graph-based memory system for AI agents that enables persistent information storage between conversations.
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    An enhanced MCP server that provides intelligent memory and task management for AI assistants, featuring semantic search, automatic task extraction, and knowledge graphs to help manage development workflows.
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    Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.
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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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    An MCP Server providing access to Google's Firebase API, allowing natural language interaction with Firebase services and resources.
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    A local Model Context Protocol server providing backend tools for AI agents to manage projects and tasks with persistent storage in SQLite, enabling structured tracking of project tasks with dependencies, priorities, and statuses.
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    Gives AI coding assistants persistent memory, safety controls, and project awareness by tracking coding sessions, protecting critical files from modifications, and managing approval workflows with automatic changelog generation.
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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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    A Model Context Protocol server for Claude Desktop that provides structured memory management across chat sessions, allowing Claude to maintain context and build a knowledge base within project directories.
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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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    Enables AI assistants to search YouTube for videos, channels, and playlists while retrieving detailed analytics and metrics through the YouTube Data API v3. Supports advanced filtering options and provides comprehensive statistics for content discovery and analysis.
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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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    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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