developer tools를 위한 엄선된 MCP 서버 컬렉션을 찾아보세요. 14595개의 서버를 탐색하고 필요에 맞는 완벽한 MCP를 찾아보세요.
Executes Python code within ephemeral Daytona sandboxes, facilitating tasks such as code execution, file manipulation, and web server previewing.
Connects to Microsoft SQL Server databases and executes SQL queries.
Streamlines the development and deployment of tools and prompts for AI model interaction.
Connects an MCP client with Sonic Pi, enabling music creation through English.
Visualizes and analyzes directory structures, enabling AI assistants to understand and navigate project structures efficiently.
Recommends location-based places within South Korea using the Kakao Map API.
Manage multiple Kubernetes clusters from a centralized control plane.
Integrates Linear as a context server for Zed's Assistant.
Integrates the Model Context Protocol (MCP) into Express applications with lightweight stateful, stateless, and SSE middleware.
Provides test results context to AI agents by connecting them to Currents.
Connects the ChatGPT macOS app to MCP servers.
Automates interactions with the Aptos Build platform for managing API keys and other build-related actions.
Enables AI agents to access coding rules directly from GitHub repositories, eliminating the need for local rule files.
Orchestrates a comprehensive spec-driven development workflow, integrating requirements, design, implementation, and validation within an MCP client.
Manages feature flags and configurations within ConfigCat through its public management API.
Provides AI agents with persistent, searchable, and versioned long-term memory that endures across conversations and tools.
Empowers AI agents and developers to comprehend and interact with codebases using a retrieval-augmented generation server.
Extends AI assistant memory by leveraging Gemini's context caching to load and query large codebases, documentation, and PDFs.
Exposes the Open Targets Platform GraphQL API as a comprehensive suite of tools for Model Context Protocol (MCP) compatible clients.
Automates prompt engineering to refine and optimize interactions with large language models across multiple providers.
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