Studio Rust
Enables communication between Roblox Studio and Claude Desktop via a plugin, allowing LLMs to interact with and modify the Roblox environment.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables communication between Roblox Studio and Claude Desktop via a plugin, allowing LLMs to interact with and modify the Roblox environment.
Delivers Svelte developer documentation and context to Large Language Models via Model Context Protocol (MCP) endpoints.
Provides line-oriented text file editing capabilities through a standardized Model Context Protocol (MCP) API.
Integrates TickTick task management with MCP clients like Claude for enhanced interaction.
Enables interaction with Trello boards via the Model Context Protocol.
Provides a JavaScript client for interacting with the txtai API, enabling semantic search and language model workflows in JavaScript applications.
Enables Python developers to integrate with the Unifai AI platform for dynamic tools and agent communication.
Integrate Universal Tool Calling Protocol (UTCP) capabilities directly into the Model Context Protocol (MCP) ecosystem through a versatile, all-in-one server.
Conduct in-depth cryptocurrency research locally using multiple data sources.
Downloads entire websites, preserving structure and converting links for local use.
Enables remote control of Adobe After Effects compositions, text, shapes, solids, and properties via the Model Context Protocol using ExtendScript.
Generates images from text prompts using the Replicate API, designed for use with MCP clients like Cursor.
Provides a Model Context Protocol (MCP) server for interacting with the App Store Connect API.
Provides a secure runtime environment for fully-autonomous AI agents, designed for enterprise-grade deployment.
Curates a list of Model Context Protocol (MCP) servers specifically for cryptocurrency-related applications.
Enables analysis and visualization of AWS cloud spending data using Anthropic's Claude model as an interactive interface.
Enables Large Language Models to securely query and analyze BigQuery datasets through a standardized Model Context Protocol interface.
Enables LLM programs to query and control Genital Interface Devices within the Buttplug.io ecosystem.
Enables AI agents to programmatically generate images with ComfyUI using the Model Context Protocol.
Empowers local developers with efficient internet search and content retrieval for Large Language Models, saving tokens.
Demonstrates how to enhance ChatBot applications using Amazon Bedrock with the Model Context Protocol (MCP) to enable seamless integration with external systems and data sources.
Provides a universal server for processing, converting, and automating various document formats through a unified API.
Showcases a .NET eCommerce application with semantic search, managed context protocol (MCP), and reasoning models.
Demonstrates building a functional Model Context Protocol (MCP) server for integrating with LLM clients.
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.