AI Infra Real-Time Agent
Enables real-time tool execution and structured knowledge retrieval for AI clients using an MCP-based infrastructure.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Enables real-time tool execution and structured knowledge retrieval for AI clients using an MCP-based infrastructure.
Explores and demonstrates artificial intelligence concepts through proof-of-concept implementations.
Demonstrates the Model Context Protocol (MCP) using a locally hosted LLM and Java Spring Boot.
Enables AI models to dynamically create and execute custom tools through a meta-function architecture.
Provides an AI Pair Programmer server offering various AI-powered tools for code development and analysis.
Aids in optimizing requirement engineering workflows by leveraging AI-driven insights and innovative coding methodologies.
Monitors and compares the response times of GitHub Copilot and other AI models.
Provides real-time stock market data and financial insights through natural language queries.
Facilitates the creation and deployment of AI-powered tools and agent-based chat systems through a modular, open-source framework.
Provides practical code snippets and examples for integrating various artificial intelligence features and models.
Generates videos from text prompts and images using AI models.
Provides narrative, character, and archetypal storytelling tools to AI assistants.
Automates email sending and Google Calendar event creation using natural language prompts.
Browse and discover open-source AI agent and MCP orchestration tools.
Manages hierarchical tasks for AI assistants, providing a cognitive prosthetic for focus and context during complex problem-solving.
Automates commit message creation and simplifies Gitflow workflows using staged files.
Checks the status of Airbyte connections through the Claude Desktop MCP protocol.
Enables Large Language Models (LLMs) to interact with and control Android devices.
Enables connection to Airtable data from Claude Desktop using CData JDBC Drivers via a read-only Model Context Protocol (MCP) Server.
Facilitates AI agents in connecting with and manipulating AITable datasheets.
Integrates the AivisSpeech text-to-speech engine with AI assistants and applications for natural Japanese speech synthesis.
Bridges AI agents and the Akash Network, enabling AI models to deploy applications and manage deployments.
Enables AI assistants to query and manage Prometheus Alertmanager resources programmatically and securely.
Provides a reproducible lab environment for experimenting with the Model Context Protocol (MCP) against Alfresco Community Edition using Docker.
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.