Connect Cursor Cloud Agent to ChatGPT, Claude and Gemini

Fastest day

940ms

Slowest day

1420ms

14-day trend

Stable0%

Cursor Cloud Agent Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_WJUsxIeBdLTUmOiGm9g0ZUKYn9WLxdIjkfcta731/mcpCopy

Claude Desktop

Follow the steps below to connect in seconds.

1. 1In Claude Desktop, open Settings → Connectors.
2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3. 3Click Add and start a new chat — Cursor Cloud Agent capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "cursor-cloud-agent-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_WJUsxIeBdLTUmOiGm9g0ZUKYn9WLxdIjkfcta731/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Cursor Cloud Agent in Claude and other AIs

See all the AI clients this connector works with ↑

• 01

  Engineering Teams

  Automate repetitive coding tasks by spinning up agents that work directly in your repos.

• 02

  DevOps

  Orchestrate autonomous code changes, pull requests, and reviews across multiple repositories.

• 03

  Platform Teams

  Monitor agent usage and token consumption to manage costs.

• 04

  Developers

  Delegate specific coding tasks to cloud agents and track the results from a chat interface.

• 01

  How do I get my Cursor API key?

  Go to the Cursor Dashboard → API Keys section to create or manage your API key. The key starts with crsr_ and can be either a user API key or a service account API key. Copy it and paste it into the API key field in the setup wizard. The key is sent as a Bearer token in the Authorization header for all API requests.

• 02

  What are Cursor cloud agents?

  Cloud agents are autonomous coding agents that run in Cursor's managed environment. You give them a prompt describing what you want (e.g. 'Add a README file to this repo'), connect one or more repositories, and the agent works autonomously. reading code, making changes, and optionally creating pull requests. You can track run status, view results, and manage the agent lifecycle through the API.

• 03

  Can cloud agents automatically create pull requests?

  Yes! When creating an agent, set the autoCreatePR flag to true and the agent will automatically create a pull request when it finishes its work. You can also filter agents by PR URL using the pr_url parameter in the list_agents capability to find agents associated with a specific PR.

• 04

  Which models are supported by cloud agents?

  Cursor cloud agents support multiple AI models including gpt-4.1, claude-sonnet-4-20250514, and gemini-2.5-pro. You can specify the model when creating an agent using the model_id parameter. If no model is specified, Cursor uses its default model. The model determines which AI processes your agent's prompts and generates code changes.

• 05

  How do I track the status of a run?

  Use the get_run capability with the agent ID and run ID to get the full status including the current state (running, completed, cancelled), duration in milliseconds, the result output, and git branch information. You can also use list_runs to see all runs for an agent. To stop a long-running run, use cancel_run. this is a terminal operation that cannot be undone.

• 06

  Can I configure MCP servers for my agent runs?

  Yes. When creating a run with the create_run capability, you can pass an mcp_servers_json parameter containing a JSON array of MCP server configurations. This allows your cloud agent to access external capabilities and resources during the run, extending its capabilities beyond the default set of capabilities.

• 07

  Are there rate limits on the Cloud Agents API?

  Yes, the Cursor Cloud Agents API enforces standard rate limiting. If you exceed the rate limit, the API returns an error and the engine surfaces the error message. For high-volume usage, consider spacing out requests and using pagination (limit and cursor parameters) when listing agents and runs. The get_agent_usage capability helps you monitor token consumption to stay within your plan's limits.

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