LI.FI
Enables cross-chain token swaps by integrating with the LI.FI API.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables cross-chain token swaps by integrating with the LI.FI API.
Simulates a Multi-Context Processing (MCP) system for efficient data handling across multiple contexts.
Organizes and manages files across directories by type, leveraging robust permission checking for secure access.
Turns scattered AI conversations into persistent, searchable knowledge by capturing insights from any AI session and making them available across all your tools.
Analyzes legal spend across diverse data sources to provide comprehensive financial insights.
Simplifies management of Model Context Protocol (MCP) servers across various clients.
Manages configurations for multiple Model Context Protocol (MCP) servers and applies them across various clients.
Provides Large Language Models with persistent memory capabilities, enabling continuous learning and knowledge retention across sessions through the Model Context Protocol.
Provides large language models with persistent, intelligent semantic memory across conversations.
Enables tool discovery and execution across multiple Model Context Protocol (MCP) servers and JavaScript functions.
Provides a persistent, semantic memory system for large language models to overcome context limitations across conversations.
Provides persistent memory and instruction management for VS Code's GitHub Copilot, ensuring it remembers user preferences and context across conversations.
Implements a high-performance, cross-platform server for the Model Communication Protocol (MCP) in modern C++.
Curates a comprehensive list of over 50 Model Context Protocol servers designed to extend AI capabilities across diverse domains.
Provides a modular and extensible tool server built on FastMCP, supporting multiple tools organized across files.
Unifies development best practices across multiple programming languages into a single, comprehensive Model Context Protocol (MCP) server.
Accesses Morpho protocol vault data across multiple blockchain networks for LLM integration.
Deploys n8n for automation using Docker and the n8n Community Proxy, enabling free cloud hosting and optional Cloudflare Tunnel integration.
Aggregates and provides access to The Ohio State University's content APIs across various campus services.
Provides a persistent memory solution using a local knowledge graph, allowing applications to remember information across interactions.
Provides a personal AI agent platform with cross-platform capabilities and Model Context Protocol (MCP) integration, leveraging Claude 3.7.
Uploads files to Alibaba Cloud OSS, supporting multiple configurations and directory specification.
Provides standardized handling of translation requests across multiple languages using Claude Sonnet 3.5.
Values personal investment portfolios across various asset classes, automates market data fetching, and generates trading insights using large language models.
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.