Py-Sound
Provides audio feedback for code completion, errors, and notifications in MCP-compatible environments.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides audio feedback for code completion, errors, and notifications in MCP-compatible environments.
Enables AI agents to automate desktop tasks by controlling mouse, keyboard, and screen interactions.
Enables AI assistants to interact with the GitHub API via PyGithub for managing repositories, issues, and pull requests.
Provides a foundational template for developing Model Context Protocol servers in Python.
Enables Claude Desktop and Gemini Cli to communicate with PyMDU via a Model Control Protocol server.
Exports PDF files to markdown format, optimized for use with Large Language Models (LLMs).
Enables structured queries for Python packages and their associated GitHub repositories.
Provides a high-performance, context-aware search engine for Python codebases supporting text, regex, AST, and semantic search.
Updates large language models with context about the most recent pytest results.
Enables LLMs to execute Python code, manage files, and interact with Python environments.
Provides a cookiecutter template to quickly bootstrap a Python-based server.
Guides aspiring programmers through Python fundamentals using an engaging space adventure narrative.
Provides a foundation for interacting with an MCP server using Python.
Extracts and analyzes Python code structures, focusing on import/export relationships, for language model integration.
Integrates Zhipu AI and Tencent Map API to provide weather queries, geocoding, and web search functionalities via command-line and web interfaces.
Unifies the latest documentation for all Python dependency managers, making it instantly searchable from your agentic IDE.
Enables interaction with the dev.to API through a message-based architecture using a Python-based server.
Executes Python code and manages Python packages within a sandboxed environment.
Generates images from text prompts using the Adobe Firefly API.
Executes Python code snippets via a standardized Model Context Protocol (MCP) API.
Provides a minimal template for creating Model Context Protocol (MCP) servers using the Python SDK.
Provides a comprehensive set of tools for Python development via the Model Context Protocol.
Orchestrates and manages diverse automated tasks, including shell commands, API calls, AI content generation, and desktop reminders, with flexible cron-based scheduling.
Provides a Model Context Protocol (MCP) server enabling AI analysis of QAnon posts for sociological research.
MCP (Model Context Protocol) servers are tools that connect AI assistants like Claude, Cursor, and other AI coding tools to external data sources, APIs, and services. They enable AI models to access real-time information, execute code, interact with databases, and perform actions beyond their base capabilities. Check out our curated collection of the best MCP servers for Cursor →
MCP servers act as intermediaries between AI assistants and external systems. When you ask Claude or Cursor to perform a task requiring external data, the MCP server handles the request, fetches the data, and returns it in a format the AI can understand and use.
When selecting an MCP server, consider:
For detailed setup guides, see our Complete MCP Server Setup Guide →
Everything you need to know about installing, using, and troubleshooting Model Context Protocol.
To install MCP servers in Cursor: 1) Open Cursor settings (Cmd+,), 2) Navigate to MCP Servers section, 3) Click 'Add Server', 4) Enter server configuration (name and command), 5) Restart Cursor. Check out our curated collection of the best MCP servers for Cursor with detailed setup guides.
MCP servers are protocol-level integrations that work across multiple AI assistants (Claude, Cursor, etc.), while VS Code extensions are editor-specific. MCP servers provide context to AI models, whereas extensions add IDE functionality. MCP is more portable and AI-focused.
Most MCP servers listed are open-source and free. Some enterprise connectors (like Salesforce or Jira) may require paid API access to the underlying service, but the MCP server code itself is usually free.
Yes! The Model Context Protocol is open standard. You can build servers in Python or TypeScript/Node.js to expose your own internal APIs or databases to Claude and Cursor.
An MCP server is a lightweight program that exposes specific capabilities (data access, tool execution, prompts) to AI assistants through a standardized protocol. MCP servers allow Claude and other AI models to securely interact with external systems like databases, APIs, file systems, and web services while maintaining security boundaries.
MCP servers connect to Claude Desktop or other MCP-compatible clients through a standardized JSON-RPC protocol. When you configure an MCP server in Claude Desktop, Claude can access its resources (data/content), use its tools (functions to execute), and leverage its prompts (templated interactions). The protocol ensures secure, controlled access to external capabilities.
Essential MCP servers for beginners include: Filesystem (local file access), SQLite/PostgreSQL (database queries), GitHub (repository access), Brave Search (web search), and Memory (persistent context). These cover common use cases and have excellent documentation. Start with 2-3 servers and expand based on your needs.
Most MCP servers install via npm (npx) or Python (uvx/pip). Configure them in Claude Desktop's config file (claude_desktop_config.json) by specifying the command, arguments, and any required environment variables like API keys. Our directory links to each server's documentation with specific installation instructions.
MCP servers run locally on your machine with explicit permissions you configure. They can only access resources you authorize, and Claude cannot bypass these boundaries. However, always review server code, use official/verified servers when possible, limit permissions to what's necessary, and be cautious with servers that request broad access.
Resources are data sources Claude can read (files, database results, API responses). Tools are functions Claude can execute (run queries, send messages, create files). Prompts are pre-defined templates for common interactions. Most MCP servers expose one or more of these capability types.
MCP is supported by Claude Desktop (official), Cursor IDE, Continue (VS Code extension), and various community implementations. The protocol is open, so support is expanding to more AI development tools. Check our compatibility filters to find servers tested with your preferred client.
Our MCP servers directory is updated weekly with new servers, documentation improvements, and compatibility updates. We monitor GitHub releases, community contributions, and Anthropic announcements to ensure our listings reflect the latest MCP ecosystem developments.