HelloPython AI ML
Provides PyTorch AI/ML examples for Modal Context Protocol (MCP), Agent-to-Agent (A2A), RAG, and vLLM workflows, enabling reproducible and scalable pipelines for research and depl…
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides PyTorch AI/ML examples for Modal Context Protocol (MCP), Agent-to-Agent (A2A), RAG, and vLLM workflows, enabling reproducible and scalable pipelines for research and depl…
Enables AI assistants to interact with the Helm package manager for Kubernetes using natural language.
Empowers developers with an intuitive AI development tool that integrates seamlessly into their workflow through natural language interaction.
Enables AI assistants to interact with the Hive blockchain using the Model Context Protocol.
Connects AI assistants like Claude and Cursor directly to your HiveFlow automation platform.
Provides an HTTP interface for executing queries against Apache HiveServer2 instances.
Enables AI assistants to interact with Holaspirit data through a standardized Model Context Protocol (MCP) interface.
Enables AI clients to securely control Home Assistant switch devices and retrieve their states.
Provides an MCP server for HomeyPro home automation systems, enabling paginated access and comprehensive control over devices, zones, and flows.
Detects potential honeypot tokens across Ethereum, BNB Smart Chain, and Base networks.
Exposes project-specific development tools like linters and tests to coding agents via a simple YAML configuration, enabling easy setup, execution, and sharing.
Provides daily horoscope readings and fortune telling for all zodiac signs.
Connects Claude to LM Studio for local AI-powered code analysis, generation, and creative tasks.
Dynamically create and update HTML pages with real-time synchronization across connected clients.
Analyze and visualize Solana blockchain transactions using natural language queries.
Enables AI assistants to control Philips Hue smart lighting systems with natural language via a modern Model Context Protocol (MCP) server.
Accelerates HuggingFace model downloads and integrates them into various AI development clients.
Provides seamless programmatic access to Human Protein Atlas data, offering comprehensive information on protein expression, localization, and pathology.
Enhances AI coding agents by providing them with continuously updated and contextually relevant documentation to improve their performance.
Integrates with Hyperskill to enable AI agents to explain programming topics using Hyperskill's learning resources.
Enables Claude or other AIs to interact with Iaptic data to answer questions about customers, purchases, transactions, and statistics.
Manages macOS calendars using natural language processing via a single agent-based interface.
Invokes task chains of the iFlytek SparkAgent Platform using MCP Server.
Analyzes IL2CPP dump.cs files from Unity games using an agentic RAG system and Model Context Protocol.
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.