developer tools向けの厳選されたMCPサーバーコレクションをご覧ください。12982個のサーバーを閲覧し、ニーズに最適なMCPを見つけましょう。
Provides a unified platform that combines centralized access control with intelligent tool discovery for MCP servers.
Enables AI assistants to interact with the Cocos Creator editor through a standardized Model Context Protocol (MCP) server.
Enables agentic AI workflows for developers using Docker containers and Markdown prompts.
Provides up-to-date documentation for thousands of libraries directly within your AI code editor via the Model Context Protocol.
Enables Claude to execute code using E2B sandboxes via the Model Context Protocol.
Connects to Kubernetes, providing a Model Context Protocol (MCP) server for interacting with Kubernetes resources.
Enables natural language interaction with KiCad for project management, PCB design analysis, and more using the Model Context Protocol.
Dynamically generate mermaid diagrams and charts using AI.
Provides a local, open-source coding assistant experience similar to Claude Code, leveraging the Vercel AI SDK.
Manage and automate YouTube resources through a command-line interface or a Model Context Protocol (MCP) server.
Integrates cutting-edge LLM/GenAI models into Unreal Engine for game development and interactive experiences.
Enables building Model Context Protocol (MCP) servers and clients in .NET for AI assistant integration.
Automates browser interactions through Puppeteer for both new and existing Chrome instances.
Connects IoT devices to AI Large Language Models by translating MCP protocol to MQTT, enabling natural language control of hardware.
Enables AI agents to interact with multiple EVM-compatible networks through a unified interface.
Enables AI models to control macOS with mouse, keyboard, screen, and window management.
Enables AI-powered coding tools to access Feishu documents via a Model Context Protocol server.
Enables AI assistants in Cursor, VS Code, Claude Code, or any MCP-enabled IDE to autonomously manage Home Assistant configurations, automations, dashboards, and themes using natural language.
Empowers AI development teams by serving as a central knowledge hub, automating demand analysis, UI asset extraction, and fostering collaboration across diverse AI assistants.
Enables AI assistants to manage and operate Terraform environments through the Model Context Protocol (MCP).
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