Deep Web Research
Enables enhanced web research capabilities for large language models through intelligent search queuing and advanced content extraction.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables enhanced web research capabilities for large language models through intelligent search queuing and advanced content extraction.
Exposes DigitalOcean App Platform functionality through standardized tools for MCP clients.
Simplifies the installation and management of MCP servers across multiple platforms.
Provides a browser automation server using DrissionPage and FastMCP, offering a rich set of browser operation APIs for AI integration.
Automates Excel file creation, viewing, and modification using LLM capabilities via a C++-based MCP server.
Enables seamless interaction between GIMP and AI models for intelligent image editing workflows.
Enables management of GitHub Projects programmatically through the Model Context Protocol (MCP) interface.
Connects OpenAI's GPT-5 API to Claude Code environments for advanced AI capabilities.
Enables LLMs to interact with and manipulate JSON data through standardized tools.
Enables LLMs to interact with on-disk documents through agentic RAG and hybrid search powered by LanceDB.
Enables AI applications to access the Lara Translate API for seamless and high-quality translations.
Discovers and analyzes websites implementing the llms.txt standard.
Provides a privacy firewall for large language models, automatically detecting and redacting sensitive information from PDF documents before processing.
Provides a foundation for building Model Context Protocol (MCP) servers with TypeScript.
Provides a persistent memory system for Model Context Protocol (MCP) using libSQL, enabling vector search and knowledge management.
Enables running multiple isolated instances of MCP servers with unique configurations and namespaces.
Provides a central repository for biomedical ontologies, offering a single point of access to their latest versions.
Enables image generation and editing through OpenAI's GPT-4o/gpt-image-1 APIs using the Model Context Protocol.
Enables querying OpenAI models directly from Claude using the MCP protocol.
Enables semantic search and API request execution for OpenAPI specifications, integrating seamlessly with Claude Desktop.
Transforms any OpenAPI 3.x specification into an AI-friendly Machine-to-Computer Protocol (MCP) tool server.
Provides LLMs with efficient access to package documentation across multiple programming languages.
Enables Large Language Models to interact with Python environments, execute code, and manage files.
Connects Claude Desktop to a Redmine instance, enabling interaction with Redmine's API via 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.