Copy Web UI
Downloads and analyzes websites for UI/UX inspiration by capturing complete HTML content and resources.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Downloads and analyzes websites for UI/UX inspiration by capturing complete HTML content and resources.
Extracts specific lines from text content, preserving formatting and newlines.
Integrates AI agents with the Cyber decentralized knowledge graph, enabling interactions, cyberlink creation, and IPFS content retrieval.
Enables Large Language Models to interact with the Deepwriter AI platform for project management and content generation.
Retrieves and cleans web content, optimizing it for consumption by Large Language Models.
Provides programmatic access to a comprehensive collection of developer roadmaps and their detailed content.
Integrates DevHub CMS with Large Language Models through the Model Context Protocol.
Manages and organizes conversational content on an MCP server using templated recording features.
Automates interactions with the Dev.to platform, enabling content creation, article management, and user profile interactions through intelligent agent communication.
Enables AI tools and LLMs to interact with your Directus instance via the Model Context Protocol (MCP) for content management and data analysis.
Recursively fetches and extracts content from web pages for LLM consumption.
Converts documents between various formats while preserving content fidelity.
Integrates Emlog blog systems, enabling AI assistants to interact with blogs via a standardized Model Context Protocol interface.
Provides AI assistants with comprehensive, reliable access to EVE University Wiki content, including automatic Wayback Machine fallback.
Validates code and content against official Model Context Protocol specifications, ensuring technical accuracy and preventing misinformation.
Bridges FAL AI's powerful image and video generation capabilities with MCP-compatible clients for seamless content creation.
Extracts and transforms web content into various formats, including rendered HTML, Markdown, and text from media files.
Retrieves web content as Markdown and saves it to a local file.
Analyzes food images to detect items, calculate calories and protein content, and answer nutrition-related questions using AI.
Generates high-quality educational content tailored to students' knowledge levels and interests using a Model Context Protocol (MCP) server.
Provides GitHub repository context to AI models, enabling them to access file contents, structure, and more.
Generates prompts based on a Git repository's content using a Model Context Protocol (MCP) server.
Empower AI agents to visualize and capture web content through device-specific screenshots.
Scrapes and crawls visible text content from public web pages using a lightweight HTTP module designed for the VS Code Model Context Protocol.
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.