developer tools를 위한 엄선된 MCP 서버 컬렉션을 찾아보세요. 20916개의 서버를 탐색하고 필요에 맞는 완벽한 MCP를 찾아보세요.
Enables AI assistants to access and interact with real-time transport alerts from Transport for NSW.
Enables LLMs to compose and send emails via the Resend API.
Caches a codebase as a graph to provide LLMs with efficient code memory.
Provides programmatic control over tmux sessions using the Model Context Protocol.
Centralizes Model Context Protocol (MCP) servers in a home lab environment using Docker, Traefik, and SuperGateway.
Converts text to speech using OpenAI's API from the command line.
Compose and generate asynchronous API clients and Model Context Protocol (MCP) servers from OpenAPI specifications effortlessly.
Provides recipes within an MCP-compatible client environment.
Transforms an OpenAPI service into a Model Context Protocol (MCP) server.
Provides an AI-powered memory system for Claude Code, maintaining persistent and evolving contextual understanding across coding sessions.
Enables AI assistants and developers to manage JasperReports Server operations including authentication, resource management, report execution, and job scheduling via the Model Context Protocol.
Integrates AI capabilities into business applications on the .NET Platform, enabling AI-powered interactions with processed and stored business events.
Build a reliable trading assistant for Forex, Stocks, and Crypto with advanced indicators and Pine Script tools for smart trading decisions.
Integrate with the Slovensko.Digital Autoform service to search and retrieve information on Slovak corporate bodies.
Establish a centralized collaboration inbox for AI agents and runtimes using the Human Agent Protocol (HAP).
Enables Claude AI to manage Dida365/TickTick tasks using natural language commands.
Empowers AI agents with real trading capabilities on Bybit perpetual futures through a managed Model Context Protocol server.
Enables multi-agent AI collaboration for real-time music creation and live-coding jam sessions.
Indexes project documentation, code, and files to construct a semantic graph memory, offering tools for search, knowledge management, tasks, and skill recall.
Assesses system landscapes, recommends AI integration patterns, and scaffolds production-ready code for connecting AI into enterprise systems.
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