Context Provider
Provides AI models with persistent tool context, ensuring consistency across chat sessions and eliminating the need to re-establish context.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Provides AI models with persistent tool context, ensuring consistency across chat sessions and eliminating the need to re-establish context.
Enables AI models, such as LM Studio, to securely interact with local data and custom tools by implementing the Model Context Protocol.
Manages AI tool context centrally to reduce sharing costs and improve development productivity.
Connects data warehouses to AI assistants and agents, enhancing LLM understanding of data structure and business context.
Manages development context and workflow through a Model Context Protocol (MCP) server implementation.
Retrieves on-chain Ethereum smart contract information locally via the MCP protocol for use with AI tools like Cursor.
Automates recording and managing AI conversations, integrating with Claude Desktop, VSCode, and Cursor for enhanced knowledge management and productivity.
Automates the deployment and management of Coolify infrastructure through natural language conversations with AI assistants.
Automates container image vulnerability patching through a Model Context Protocol (MCP) server.
Provides a core framework for constructing MCP-compliant AI agents and tools using PowerShell.
Enables AI assistants to interact with and control Coreflux MQTT brokers.
Enables AI applications to access real-time B2B data about companies, employees, and job postings.
Improves AI reasoning by enabling it to recursively argue with itself through a Chain-of-Recursive-Thoughts process.
Enables AI tools to access and analyze business data by integrating with Coupler.io data flows.
Deploys a customizable Model Context Protocol (MCP) server on Cloudflare Workers for integrating custom AI tools.
Provides a Model Context Protocol server for integrating AI assistants with Black Duck Coverity Connect static analysis.
Integrates AI assistants with Cozi Family Organizer to manage family members, lists, and calendar events.
Enables AI applications to interact with Crawlab's functionality through natural language.
Transforms vague ideas into production-ready servers with minimal effort through AI-guided workflows and intelligent templates.
Facilitates the setup of multi-agent AI systems using the crewAI framework for effective collaboration on complex tasks.
Provides an interface to CRIC Property AI functionalities for accessing industry insights, knowledge bases, and more.
Provides AI assistants with access to Crunchbase data for company insights, funding information, and people data.
Provides an MCP server to track real-time and historical data for major crypto-related stocks, aiding AI agents in investment analysis.
Enables Claude to interact with Ethereum and EVM-compatible blockchains.
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.