UniFi Network
Exposes a UniFi Network Controller as a set of programmable tools accessible via the Model Context Protocol (MCP).
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Exposes a UniFi Network Controller as a set of programmable tools accessible via the Model Context Protocol (MCP).
Converts Web API interfaces into standardized tools accessible by AI assistants through simple configuration.
Simplifies the integration of Model Context Protocol (MCP) functionality into Elixir-based Phoenix or Bandit servers.
Tracks cryptocurrency whale transactions using the Whale Alert API.
Enables Python script execution within a running Abaqus/CAE GUI and retrieves messages from its log area via MCP tools.
Enables natural language interaction with Actual Budget financial data through large language models using the Model Context Protocol.
Executes tasks using Model Context Protocol (MCP) tools via Anthropic Claude, AWS BedRock, and OpenAI APIs.
Scales software development using controllable, recursive agent flows driven by OpenAI's Codex to build features from the ground up.
Generates web scrapers for various websites by leveraging Cursor AI and Model Context Protocol (MCP).
Provides tools for accessing and interacting with Alibaba Cloud's observability products like SLS and ARMS.
Converts PDF, Word, and Excel documents into Markdown format, offering a high-performance server solution with both Model Context Protocol (MCP) and RESTful API support.
Simplifies adding authentication and authorization to Node.js MCP servers.
Exposes Buildkite pipeline, build, and job information to tools like Claude Desktop and GitHub Copilot.
Enables Large Language Models to interact with cheminformatics functionalities, performing tasks like compound identification, structure conversion, and property calculation.
Enhances language models with specialized prompts fetched from the L1B3RT4S repository to potentially bypass limitations.
Provides a standardized interface for accessing cryptocurrency market data and exchange information from the CoinMarketCap API.
Facilitates structured, iterative reasoning for complex problem-solving and analysis through an advanced Model Context Protocol server.
Provides real-time cryptocurrency analysis via CoinCap's API, enabling analysis of market trends and tracking of historical data.
Exposes Dify workflows as a Model Context Protocol (MCP) server for integration with AI clients.
Enables access to the esa.io API through the Model Context Protocol (MCP).
Provides a REST API for managing VMware ESXi/vCenter virtual machines using the Model Control Protocol.
Provides fast, scriptable access to Windows `.evtx` logs through a Model Context Protocol server.
Provides AI-powered web search and summarization with citations by leveraging the Gemini API's grounding feature.
Connects large language models to the GeoServer REST API, enabling AI assistants to interact with geospatial data and services.
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.