One Inch
Executes cross-chain token swaps using 1inch Fusion+ and 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.
Executes cross-chain token swaps using 1inch Fusion+ and Model Context Protocol (MCP).
Unify your digital life across platforms like Steam, YouTube, Bilibili, and Spotify, enabling AI assistants to provide truly personalized and contextual interactions.
Analyze startup investment risks using AI-powered assessment across multiple categories, leveraging the Model Context Protocol.
Enables AI agents to create and manage simple, persistent reminders for themselves across sessions, similar to human voice assistant reminders.
Enables AI assistants to interact with the Rohlik Group's online grocery delivery services across multiple countries.
Provides daily activity and graduate metrics across multiple Solana launchpads.
Integrate Sunra.ai's AI model deployment and running capabilities into applications across multiple programming languages.
Provides a unified platform for benchmarking, competing, and evolving agentic AI across various game environments, tools, and workflows.
Enables AI models and MCP clients to access, analyze, and derive insights from meetings across Google Meet, Zoom, and Microsoft Teams.
Delivers real-time token prices from Uniswap V3 across multiple blockchain networks.
Fetches job opportunities and freelancer data from the Useme.com freelance platform for AI assistants.
Streamlines development workflows by providing consistent environments, tooling configurations, and coding patterns for modern AI Agentic coding across multiple repositories.
Inspect wallet balances and onchain activity across major EVM chains and Solana, empowering AI agents with flexible outputs.
Synchronizes work activities across Harvest, Linear, and Slack, featuring automated daily standups and AI-powered time tracking.
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.