Teamtailor
Integrates with the Teamtailor API to provide candidate data through the Model Context Protocol.
Browse 6,627+ Model Context Protocol servers for Claude, Cursor, and VS Code. Find the perfect tools for your AI workflow.
Integrates with the Teamtailor API to provide candidate data through the Model Context Protocol.
Enables seamless integration between Large Language Models and Teamwork.com for project management operations.
Enables interaction with Tecton clusters, feature store management, and Tecton CLI command execution.
Provides a server to interact with the Tehran Stock Exchange for real-time and historical stock data.
Implements a Model Context Protocol server for Tekton.
Enables LLM applications to perform real-world telephony operations such as voice calls and SMS messaging using the Vonage API.
Provides comprehensive access to Telnyx's telephony, messaging, and communication services through a Model Context Protocol server.
Provides philosophical guidance and mentorship using rationalist thinking, Stoic philosophy, and smart contracts.
Provides an MCP server facilitating interaction with the Tembo Cloud platform API.
Provides reliable and durable mathematical operations by bridging Model Context Protocol (MCP) tools with Temporal's Nexus RPC framework.
Manages temporary email addresses and messages through the ChatTempMail API for integration with MCP clients.
Delivers Tencent Cloud SDK documentation and API resources to Large Language Model (LLM) tools, enhancing AI agent understanding and interaction with Tencent Cloud services.
Enables AI assistants to interact with security data pipelines and map security data to the Open Cybersecurity Schema Framework (OCSF).
Enables AI agents to control terminal sessions through persistent tmux-based sessions, featuring a real-time web interface and comprehensive security controls.
Enables execution of terminal commands within a Model Context Protocol environment.
Provides a secure and controlled terminal server implementation for Model Context Protocol.
Facilitates Terrakube operations by enabling workspace management, variable handling, module operations, and organization management.
Connects to the Tesla Fleet API, enabling AI assistants to control and interact with Tesla vehicles.
Enables querying of Brazilian treasury bond data using natural language through an MCP-compatible server.
Integrates agents with the TESS AI platform using the Model Context Protocol (MCP).
Query your Tesla vehicle data using natural language through the Tessie API.
Provides a simple server for testing Model Context Protocol (MCP) clients.
Demonstrates and tests various mechanisms of the Model Context Protocol (MCP) using its TypeScript SDK.
Provides a Model Control Protocol (MCP) service with tools for Cursor and Claude applications.
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.