TeamAI MCP Server | TeamAI Help Center

The TeamAI MCP (Model Context Protocol) server provides a standardized interface that allows any compatible AI model or agent to programmatically access and manage your TeamAI workspace data, including agents, tools, and configurations.

Connect to our MCP server using the streamable HTTP transport in Cursor, Windsurf, Claude Desktop, and other MCP-compatible clients to seamlessly integrate TeamAI's powerful agent management capabilities into your development workflow.

Transport Support

Current: Streamable HTTP (/api/mcp/mcp)

Setup Instructions

> Note: Remote MCP connections are still evolving technology. If you experience connection issues, try restarting your client or temporarily disabling and re-enabling the TeamAI MCP server.

Claude Desktop

Team/Enterprise (Claude.ai)

Navigate to Settings in the sidebar
Scroll to Integrations and click Add more
Enter the following:
1. Integration name: TeamAI
2. Integration URL: https://api.teamai.com/mcp/mcp
Make sure to enable the tools in any new chats

Free/Pro (Claude Desktop App)

Open the file ~/Library/Application Support/Claude/claude_desktop_config.json
Add the following configuration
{ "mcpServers": { "teamai": { "command": "npx", "args": ["-y", "mcp-remote", "https://api.teamai.com/mcp/mcp", "--header", "Authorization:Bearer YOUR_API_TOKEN"] } }}
Restart the Claude Desktop app

Cursor

Open Cursor and go to Settings → MCP
Click Add new global MCP server
Add the following configuration
{ "mcpServers": { "teamai": { "command": "npx", "args": [ "mcp-remote", "https://api.teamai.com/mcp/mcp", "--header", "Authorization:Bearer YOUR_API_TOKEN" ] } }}
Restart Cursor to activate the connection

TeamAI

You can also connect external MCP servers as tools within your TeamAI workspace, allowing your agents to access external data sources and services.

Navigate to Tools
1. Go to your workspace
2. Click on Tools in the sidebar
3. Click Create Tool
Select MCP Server
1. Choose MCP Server as the tool type
2. This provides a simplified interface optimized for MCP connections
Configure Basic Information
1. Name: Give your MCP server a descriptive name
2. Description: Explain what data or services this MCP server provides
3. Group: Optionally organize into folders for better management
Set the MCP Server URL
1. MCP Server URL: Enter your MCP server endpoint
Configure Headers (if needed)
1. Click Add Header to configure authentication or custom headers
2. Common headers: Authorization, Content-Type, Accept, User-Agent
3. Hidden headers: Toggle on to securely store sensitive values like API keys
4. Example: Authorization: Bearer your-api-token

Visual Studio Code

Press Ctrl/Cmd + Shift + P and search for MCP: Add Server
Select Command (stdio)
Enter the following configuration
npx mcp-remote https://api.teamai.com/mcp/mcp --header "Authorization:Bearer YOUR_API_TOKEN"
Enter the name TeamAI and press Enter
Activate using MCP: List Servers → TeamAI → Start Server

Windsurf

Press Ctrl/Cmd + , to open settings
Navigate to Cascade → MCP servers
Select Add Server → Add custom server
Add the following configuration
{ "mcpServers": { "teamai": { "command": "npx", "args": ["-y", "mcp-remote", "https://api.teamai.com/mcp/mcp", "--header", "Authorization:Bearer YOUR_API_TOKEN"] } }}

Zed

Press Cmd + , to open settings
Add the following to your configuration
{ "context_servers": { "teamai": { "command": { "path": "npx", "args": ["-y", "mcp-remote", "https://api.teamai.com/mcp/mcp", "--header", "Authorization:Bearer YOUR_API_TOKEN"], "env": {} }, "settings": {} } }}