VectorCode
Indexes code repositories to provide context to LLMs for improved code completion and understanding.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Indexes code repositories to provide context to LLMs for improved code completion and understanding.
Analyzes software composition for vulnerabilities and malicious packages using policy-as-code.
Provides a security-oriented runtime for executing WebAssembly Components through the MCP protocol, enhancing AI agent capabilities.
Automates the publishing of Markdown articles to WeChat official accounts with customized themes.
Provides a Java-based server and management platform for Xiaozhi ESP32 devices, enabling device monitoring, voice customization, role switching, and dialogue management.
Simplifies building backend applications in Go with modularity and observability.
Provides a self-hosted, minimal notes application for organizing markdown-based notes with full-text search.
AWS MCP server for natural-language access to cost, usage, budgets, and optimization data.
Searches for train tickets on the 12306 platform using the Model Context Protocol.
Provides access to A-share market data through the Model Context Protocol (MCP).
Programmatically controls Android devices via ADB, exposing management capabilities to MCP clients.
Facilitates searching and downloading documents from Anna's Archive as an MCP server or command-line interface tool.
Facilitates rapid development of AI-native applications through model invocation, workflow orchestration, and application deployment.
A curated list of resources focused on the security aspects of the Model Context Protocol (MCP).
Provides a lightweight, zero-overhead implementation of the Model Context Protocol (MCP) server directly in Bash.
Enables any LLM to interactively debug code in any language through MCP and a VS Code Extension.
Offers documentation and best practices for effectively using and extending Cline's capabilities.
Identifies cloud risks, tests security vulnerabilities, and enhances cloud protection for public cloud tenants.
Unifies enterprise search and collaboration by connecting applications and data into a single interface.
Index, search, and analyze code repositories with large language models using a Model Context Protocol server.
Fetches up-to-date documentation and code examples for libraries directly into LLM prompts.
Quickly scaffolds Python projects for Model Context Protocol (MCP) servers.
Facilitates interactive data exploration by turning complex datasets into actionable insights.
Provides a Model Context Protocol (MCP) server for interacting with dbt projects.
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.