Spring Bridge
Converts REST endpoints from Spring Boot applications into an MCP server.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Converts REST endpoints from Spring Boot applications into an MCP server.
Demonstrates implementing Server-Sent Events (SSE) and Model Context Protocol (MCP) tooling with Spring Boot for real-time data streaming and AI integration.
Provides up-to-date information about Spring projects sourced from api.spring.io.
Enables searching of Spryker packages and their code content on GitHub using natural language queries.
Enables AI agents to interact with SpurtCommerce APIs for e-commerce search and browsing.
Manages sequential thinking sessions and thoughts through multiple interfaces.
Provides programmatic access to SQLMap's powerful SQL injection testing capabilities through a standardized interface for automated security assessments.
Implements a Model Context Protocol server using Server-Sent Events (SSE), designed for deployment with Netlify Edge Functions.
Enables real-time, secure communication with LLM hosts via Server-Sent Events using Bearer token authentication.
Connects STDIO-based Model Context Protocol (MCP) clients with SSE-based MCP servers, bridging different transport protocols.
Provides a basic example of a Server-Sent Events (SSE) server implementation for the Model Context Protocol (MCP).
Connects to remote Model Context Protocol (MCP) servers over SSH, enabling secure access to MCP tools.
Manages multiple SSH connections simultaneously with connection monitoring and command execution capabilities.
Facilitates remote server management by executing commands via SSH using the Model Context Protocol (MCP).
Provides an MCP server interface to interact with SpatioTemporal Asset Catalog (STAC) APIs for geospatial data discovery and access.
Locates the nearest error in JavaScript bundles (without sourcemaps) and leverages an LLM to check for codebase matches.
Facilitates the integration of stackzero-labs/ui components by running a Model Context Protocol (MCP) server for applications.
Connects to the Stakpak API and provides infrastructure code generation.
Enables control and management of Standard Bots routines via an MCP server.
Enables interaction with the Stape API using AI assistants and AI-powered IDEs.
Provides comprehensive astrology services, including zodiac information queries, horoscope analysis, and compatibility testing.
Interacts with the SWAPI Star Wars API to provide data on characters, planets, films, species, vehicles, and starships.
Integrates Model Context Protocol (MCP) functionality into a Starlette web application using Server-Sent Events (SSE).
Generates and manages activity reports for GitHub repositories, including stars, commits, and issues.
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.