Discover our curated collection of MCP servers for developer tools. Browse 20598 servers and find the perfect MCPs for your needs.
Provides isolated Docker environments for secure code execution and development environment setup.
Enables LLMs to interact with web pages by providing browser automation capabilities, including screenshot capture and JavaScript execution.
Build intelligent, context-aware agents with flexible workflow management, logging, and execution capabilities using this TypeScript port of the MCP Agent framework.
Provides secure database access capabilities for LLMs by integrating with MySQL databases.
Enables AI models and agentic applications to interact with Apache Kafka for message publishing and consumption.
Facilitates the installation, configuration, repair, and uninstallation of MCP servers.
Provides D3 visualization documentation, chart recommendations, and code generation through the MCP protocol.
Enables Large Language Models to analyze memory dumps and perform memory forensics through a conversational interface.
Connect LangChain.js-compatible LLMs with MCP servers for building AI agents with dynamic tool access and multi-server support.
Serves AI agents with comprehensive context, documentation, and intelligent development assistance for the HeroUI component library via a Model Context Protocol (MCP) server.
Provides a comprehensive server for developing BASIC and Assembly Language programs for the Commodore 64.
Integrates Atlassian Cloud products like Confluence and Jira into the Model Context Protocol ecosystem, enabling AI models to access and interact with project and documentation data.
Provides an MCP server to enable AI assistants to interact with Jira for issue, project, board, and user management.
Automate human-like operations on Windows WeChat to connect, search contacts, and send messages, supporting bulk messaging and LLM integration.
Provides example Model Context Protocol (MCP) servers and guidance for integration with AI tools like GitHub Copilot Chat.
Enhances AI coding assistants by enforcing explicit LLM evaluations for planning, code changes, and testing to ensure safer, higher-quality, and evidence-based development.
Equips AI coding assistants with live, verified Android knowledge, ensuring they build from official sources and avoid hallucinations.
Provides a high-performance knowledge graph engine combining graph storage, semantic search, logical reasoning, and continuous learning for AI systems.
Exposes Django REST Framework API documentation to AI coding agents, enabling them to assist with frontend integration code generation.
Enables coding agents to perform surgical, formatting-preserving edits on existing Microsoft Word .docx files.
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