Skip to main content
Connect your AI coding agent to ModelsLab’s account management capabilities. The Agent Control Plane MCP server is hosted — no installation required. Just add the URL and your bearer token.

Overview

The Agent Control Plane MCP server works with any client that supports the Model Context Protocol over HTTP:
  • Claude Code - Anthropic’s CLI coding assistant
  • Claude Desktop - Claude’s desktop application
  • Cursor - AI-powered code editor
  • VS Code - Via GitHub Copilot agent mode
  • Windsurf - Codeium’s AI editor
  • OpenCode - Open-source AI coding agent
  • Continue - Open-source AI code assistant
Unlike the Generation MCP server which uses API keys, the Agent Control Plane uses Sanctum bearer tokens. Get a token by calling the agent-auth tool with the login action, or via the REST API.

Getting Your Bearer Token

Before configuring your IDE, get a bearer token:
Copy the access_token from the response.
You can also use the MCP server itself to log in — the agent-auth tool’s login and signup actions work without authentication.

Using Both MCP Servers Together

For full ModelsLab access, configure both MCP servers:
ServerURLAuthPurpose
Generationhttps://modelslab.com/mcp/v7API keyImage, video, audio, LLM generation
Agent Control Planehttps://modelslab.com/mcp/agentsBearer tokenAccount, billing, subscriptions, teams

Claude Code

Edit ~/.claude/settings.json:
settings.json

Usage


Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
claude_desktop_config.json
Restart Claude Desktop after updating the configuration.

Cursor

Add to your Cursor MCP settings or edit .cursor/mcp.json in your project:
mcp.json

VS Code (Copilot Agent Mode)

Edit .vscode/mcp.json in your workspace:
mcp.json

Windsurf

Edit ~/.codeium/windsurf/mcp_config.json:
mcp_config.json

OpenCode

Edit opencode.json in your project root:
opencode.json

Continue

Edit ~/.continue/config.json:
config.json

Generic MCP Client

For any MCP-compatible client:

Environment Variables

For security, use environment variables instead of hardcoding tokens:
Add to your shell profile (~/.bashrc, ~/.zshrc):
Then reference in config:
Environment variable substitution support varies by client. Check your specific client’s documentation.

Verification

After configuring, verify the integration:

Test Connection

Ask your AI agent:

Test Model Discovery

Check for Errors

If the integration is not working, check:
  1. Token: Ensure your bearer token is valid and not expired
  2. URL: Verify the endpoint is https://modelslab.com/mcp/agents
  3. Headers: Confirm the Authorization: Bearer format
  4. Client support: Ensure your MCP client supports HTTP/SSE transport

Troubleshooting

  • Your bearer token may have expired. Get a new one via agent-auth login
  • Ensure the header format is Bearer <token> (with space after Bearer)
  • Some actions (signup, login, forgot-password) don’t need a token
  • Restart your MCP client after configuration changes
  • Check the configuration file syntax (valid JSON)
  • Verify the config file is in the correct location
  • Verify the endpoint URL is correct
  • Check your network connection and firewall rules
  • API key: Used for generation endpoints (/mcp/v7). Get from dashboard or agent-api-keys tool
  • Bearer token: Used for control plane (/mcp/agents). Get from agent-auth login

Next Steps

Tools Reference

Complete documentation for all 10 control plane tools

Agents REST API

Direct REST API documentation for the control plane