Fivetran
Enables AI assistants to manage Fivetran accounts and data integration operations through a standardized API.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables AI assistants to manage Fivetran accounts and data integration operations through a standardized API.
Bridges the gap between the FIWARE Context Broker and other services, implementing basic operations for interaction.
Automates the cleanup of feature flags in various programming languages by replacing flag calls with their configured final values.
Integrates with Flashduty APIs to provide advanced incident management and automation capabilities via the Model Context Protocol (MCP).
Provides a Flask-based server implementation for the Model Context Protocol (MCP), offering out-of-the-box security and operational features for AI agent communication.
Provides real-time flight search, status, and airline information by integrating with the Amadeus API for AI assistants.
Retrieves real-time flight tracking and status information using the AviationStack API.
Facilitates travel planning by answering complex queries using flight and hotel search capabilities.
Manages an agent-first note-taking system designed for AI collaboration and structured knowledge management.
Processes images using Florence-2 to extract text via OCR or generate descriptive captions.
Manages and interacts with the Flowcore Platform via the Model Context Protocol (MCP).
Provides an LLM service leveraging Spring Boot Java.
Provides tools for interacting with the Fluidattacks API.
Provides tools for interacting with the Flutter SDK to analyze and fix Dart/Flutter files.
Generates images from text prompts using the Flux Schnell model via Replicate.
Generates images from text prompts using the Black Forest Lab's FLUX model.
Generates images from text descriptions using Cloudflare's Flux Schnell worker API.
Enables easy FOFA data querying through a Model Control Protocol (MCP) based API server.
Enables interaction with Folderr's API for managing and communicating with Folderr Assistants using the Model Context Protocol.
Provides Claude Desktop access to comprehensive Turkish investment fund data, performance statistics, and comparisons.
Provides a comprehensive server infrastructure for food and nutrition intelligence, offering tools for data retrieval, meal planning, and dietary analysis.
Categorizes MCP Server tools into various development and management fields.
Provides access to Formula One data and statistics using the FastF1 Python library through a Model Context Protocol (MCP) interface.
Provides a language model wrapper for analyzing Formula 1 data, leveraging the Fast-F1 library.
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.