Discover our curated collection of MCP servers for developer tools. Browse 12966servers and find the perfect MCPs for your needs.
Empowers desktop AI assistants with comprehensive filesystem capabilities, including reading, writing, editing, and managing files.
Implements a Model Context Protocol (MCP) server utilizing MQTT.
Integrates command-line interfaces and AI applications with Apple Music libraries, providing ultra-fast search and smart playback.
Extracts symbol outlines from a codebase to provide LLM coding agents with necessary context.
Integrates Foxit Cloud API PDF manipulation tools into GitHub Copilot workflows within Visual Studio Code.
Manages time entries in Clockify using AI tools and natural language prompts.
Enables retrieval and management of Chrome browser tab information via the Model Context Protocol.
Enables AI assistants to control DaVinci Resolve Studio, providing advanced control over editing, color grading, audio, and more.
Enables rapid development of custom tools and data resources for large language models, particularly Claude Desktop, using intuitive Python decorators.
Executes Argo Workflows via a lightweight JSON-RPC interface.
Enables parallel execution of multiple AI coding tasks using the Aider tool.
Enables intelligent document search and retrieval from PDF collections by serving as a Model Context Protocol (MCP) server.
Provides a Model Context Protocol (MCP) implementation for managing and integrating documentation resources.
Enables Large Language Models (LLMs) to read, search, and manipulate OpenFGA stores for agentic AI and fine-grained authorization.
Retrieves requirement and defect data from the TAPD platform to support AI client applications.
Enables large language models to interact with Sidekiq queues, statistics, and failed jobs through a standardized API.
Enables AI assistants to retrieve Haskell documentation from Hackage for improved Haskell programming assistance.
Provides a test implementation of an MCP (Model Context Protocol) server for experimentation.
Enables seamless integration between Model Context Protocol (MCP) clients and servers by providing a Java-based implementation of the MCP mediator.
Empower AI agents with comprehensive codebase understanding, eliminating context loss and optimizing token usage for complex software development.
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