SFTP by CData
Exposes SFTP data as a read-only Model Context Protocol (MCP) server for querying with Large Language Models (LLMs).
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Exposes SFTP data as a read-only Model Context Protocol (MCP) server for querying with Large Language Models (LLMs).
Monitors shadow-cljs builds and provides real-time build status updates via the Model Context Protocol.
Provides automated microloans and credit management for AI agents to facilitate HTTP 402 payment transactions.
Integrates AI assistants with the Shiplogic shipping API for managing shipping rates, shipments, and tracking.
Provides a comprehensive, MCP-compliant Location-Based Service (LBS) solution for maritime scenarios, offering a rich suite of ship and port APIs for developers and AI agents.
Enables interaction with Shopify product data from Claude Desktop.
Provides AI assistants with direct access to Shopware's Admin API, enabling seamless product, category, order, and theme management.
Provides a minimal, extensible Python library for URL shortening, supporting both built-in and custom providers, with an optional MCP server for LLM integration.
Enables large language models to interact with Sidekiq queues, statistics, and failed jobs through a standardized API.
Provides a lightweight and modern chat interface for custom Model Context Protocol (MCP) servers.
Simplifies integration with Signaturit's e-signature API through an MCP server.
Power wallets and onchain apps with fast, reliable access to real-time blockchain activity and ownership data from over 60 chains.
Demonstrates how to construct an MCP server with minimal code.
Facilitates structured messaging protocol implementation for seamless client-server communication, efficient data exchange, and real-time processing.
Integrates the Model Context Protocol (MCP) into a command-line chatbot, supporting multiple tools via MCP servers and compatible with OpenAI API standard LLMs.
Execute developer commands and manage long-running processes efficiently through a configuration-driven Model Context Protocol server.
Exposes a simple FastAPI CRUD API as a set of interoperable tools using FastMCP, complete with Docker containerization and client integration instructions.
Implements a basic Model Context Protocol server using Dart.
Enables filesystem operations using natural language commands processed by a local LLM.
Facilitates simple multiple client processes using Langgraph.
Provides Language Learning Models with a safe interface to discover and execute system commands on the local machine via the Model Context Protocol.
Demonstrates calculator operations via Server-Sent Events (SSE) and Standard Input/Output (STDIO) client-server communication modes.
Connects to Snowflake, enabling programmatic SQL execution and metadata retrieval via a Model Context Protocol (MCP) server, designed to operate behind corporate proxies.
Serves files from a folder, designed for development as a simple file server.
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.