Pica
Integrates Pica with various third-party services via Model Context Protocol, enabling seamless interaction and code generation.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Integrates Pica with various third-party services via Model Context Protocol, enabling seamless interaction and code generation.
Provides secure, multi-protocol access to fitness data from services like Strava and Fitbit, enabling intelligent analysis for AI applications and agents.
Streamlines connecting AI agents to Solana-based protocols for various blockchain operations.
Enables AI agents to interact with the Solana blockchain by providing on-chain tools through a standardized interface.
Unifies developer context from various collaboration platforms into a single, accessible graph for AI assistants.
Empowers users to build and run local-first, AI-assisted, step-by-step workflows for SEO and data processing.
Analyze startup investment risks using AI-powered assessment across multiple categories, leveraging the Model Context Protocol.
Leverages Google Gemini AI to provide intelligent project planning and comprehensive code review capabilities via the Model Context Protocol.
Manages long-range tasks for AI Agents, supporting the Model Context Protocol (MCP) standard.
Automates office document processing and management with an intelligent agent system.
Discovers interesting places to explore using AI.
Enables AI assistants to break down complex tasks, track progress, and manage hierarchical task lists.
Provides audio playback functionality for AI agents, enabling notification sounds for task completion.
Enables AI assistants to control a browser through a set of tools, allowing web automation tasks.
Demonstrates MCP Poisoning Attacks affecting AI agent workflows.
Provides AI agents a standardized interface for performing Pokémon damage calculations.
Empowers AI agents with persistent memory by integrating with the PolyNeural.ai knowledge graph platform.
Enhances and structures prompts using POML best practices for more reliable AI agent workflows.
Provides a curated list of popular Model Context Protocol (MCP) servers based on usage data from Smithery.ai.
Performs intelligent, multi-layered port scanning services, optimized for AI assistants and development workflows.
Integrates and provides access to personal investment portfolio data from various sources for AI assistants.
Deploys a TypeScript Model Context Protocol (MCP) server to Azure Container Apps using SSE transport.
Collects Go runtime profiling data via the Model Context Protocol (MCP).
Automates video editing workflows in Adobe Premiere Pro using AI and natural language commands.
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.