Discover our curated collection of MCP servers for developer tools. Browse 20552 servers and find the perfect MCPs for your needs.
Provides a stateful terminal as an MCP tool server.
Enables language models to interact with Strava data, providing access to activities, athlete information, and more.
Automates end-to-end requirement management and development workflows within Feishu project systems.
Provides an AI agent for Solana blockchain development through a standardized Model Context Protocol (MCP) interface.
Manages and provides access to notes via a custom URI scheme and offers a summarization prompt and note-adding tool.
Extracts transcripts from YouTube videos via the command line.
Analyzes GitHub pull requests and manages issues as part of an automated workflow.
Provides up-to-date documentation for thousands of libraries within AI code editors via the Model Context Protocol.
Enables automated conversational phone calls using Asterisk with real-time Speech-to-Speech capabilities.
Predicts League of Legends professional esports match outcomes and analyzes summoner performance.
Provides a modular Python toolkit for creating Model Context Protocol (MCP) modules specifically designed for chemical engineering and chemistry workflows.
Integrates Google's Gemini AI with Claude Code to enable AI-to-AI collaboration and provide dual AI perspectives on development tasks.
Integrates VictoriaTraces with AI tools via the Model Context Protocol, providing programmatic access to trace data.
Scans and provides runtime protection for Model Context Protocol (MCP) servers against security vulnerabilities.
Provides structured metacognitive protocols to help AI agents recover from getting stuck without human intervention.
Provides intelligent analysis for code modernization, browser compatibility, and real-time MDN documentation queries for JavaScript/TypeScript projects.
Enables AI assistants and automation tools to manage Docker and Podman deployments, containers, stacks, and servers through Komodo.
Provides AI coding agents with persistent, cross-project memory, maintaining context, decisions, and knowledge locally across various workspaces.
Integrates fully offline text-to-speech and speech-to-text capabilities into coding assistants via the Model Context Protocol (MCP).
Enforces engineering discipline in AI-assisted software development, automating TDD, security, and deployment for production-ready code.
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