Mcp-Demos
Provides example code for understanding and implementing the Model Context Protocol (MCP).
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides example code for understanding and implementing the Model Context Protocol (MCP).
Search for MCP Servers directly from the command line.
Implements the Model Context Protocol in Go for building MCP clients and servers.
Manage and connect to multiple Model Context Protocol (MCP) servers through a unified HTTP API.
Manages and connects to multiple Model Context Protocol (MCP) servers through a unified HTTP API.
Facilitates experimentation with the Model Context Protocol (MCP) through various projects and files.
Provides a centralized collection of Model Context Protocol (MCP) servers for enhanced Cursor AI integration with PostgreSQL, Obsidian, and n8n.
Extends the core mcp python-sdk with support for typed prompts.
Serves Value Change Dump (VCD) waveform data using the Model Context Protocol.
Automates X (formerly Twitter) account management using the real browser API.
Configures, inspects, and proxies secure Model Context Protocol (MCP) servers with hot reload support.
Enables Claude and Langchain to perform web searches using the Brave API via an MCP server.
Bridges Model Context Protocol (MCP) clients using stdio with stateless HTTP servers.
Enables Claude and Langchain to perform web searches using the Tavily API.
Connect TCP devices to Large Language Models via the Model Context Protocol (MCP), enabling natural language control of hardware.
Connects Model Context Protocol (MCP) clients to GraphQL APIs, enabling interaction through standard input/output.
Generates scaffolding for Model Context Protocol (MCP) server projects.
Analyzes PCAP files to enable LLMs to query and understand network traffic, providing structured JSON responses.
Manages Model Context Protocol (MCP) servers by facilitating installation, execution, and instance management.
Provides an easy way to set up and self-host multi-tenant Model Context Protocol (MCP) servers with streamable HTTP transport, multi-client, and API key management.
Bridges Model Context Protocol (MCP) compliant clients with diverse backend services through a high-performance gateway.
Simplifies the management, configuration, and monitoring of backend services through a web-based platform.
Enables language models to dynamically discover and access new tools and capabilities through MCP servers.
Enables interaction with the Invertir Online (IOL) API via Claude Desktop using the Model Context Protocol (MCP).
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.