Node Code Sandbox
Executes arbitrary JavaScript code in isolated, ephemeral Docker containers with on-the-fly npm dependency installation.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Executes arbitrary JavaScript code in isolated, ephemeral Docker containers with on-the-fly npm dependency installation.
Enables AI agents to programmatically connect to and control an Apache Superset instance.
Facilitates the development and configuration of AI applications that integrate with Tableau Cloud and Server.
Provides AI agents with a comprehensive operating system, enabling access to tools, cognitive systems, and specialized services through the Model Context Protocol.
Enables AI assistants to deeply understand and analyze Unreal Engine source code.
Automates group conversations on WhatsApp, leveraging AI to monitor messages and provide intelligent responses.
Automates Windows desktop tasks using AutoIt functions and the Model Context Protocol (MCP).
Integrates AI assistants with the xtquant quantitative trading platform via the Model Context Protocol (MCP), providing AI access to trading data and functionalities.
Enables AI assistants to interact with and manage Azure Kubernetes Service (AKS) clusters.
Integrates OpenAI's o1 model and Flux capabilities through Model Context Protocol (MCP) servers.
Facilitates secure transactions on the Binance Smart Chain, enabling native BNB and BEP-20 token transfers.
Enhances Claude Code MCP with orchestration, reliability improvements, and self-contained execution patterns.
Enables the use of custom prompt templates with Claude AI through the Model Context Protocol (MCP).
Connects RStudio to Claude AI, enabling interactive coding sessions where Claude can execute R code and visualize results in real-time.
Provides cryptocurrency technical analysis indicators and strategies for AI trading agents.
Enables IMAP and SMTP functionality via an MCP server.
Enables AI assistants to interact with Frappe applications through the Model Context Protocol (MCP).
Generates 2D and 3D game assets from text prompts using Hugging Face AI models.
Provides AI coding assistants with persistent, cognitive memory of specific codebases, enabling long-term learning and recall across sessions.
Improves AI coding by providing better context.
Orchestrates specialized AI agents using Flowise for task automation and complex problem-solving.
Delivers professional-grade financial data analysis, technical indicators, and portfolio optimization tools directly to AI assistant interfaces for individual investors.
Connects molecular science tools to Claude AI for prompt-assisted molecule modeling and co-scientific interaction.
Enables AI assistants to interact with OmniFocus tasks and projects using natural language.
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.