MCP server gets agent chat, prompt management, and reports

Your coding assistant can now chat with your deployed agents, manage prompt versions, query your run data with TRQL, and pull a health report for any environment.

Eric Allam

Eric Allam

CTO, Trigger.dev

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When we shipped the official MCP server at Launch Week 2, it could set up a project, trigger tasks, deploy, and read runs. It does a lot more now. The server always runs at @latest, so every tool below is already available to you. Nothing to upgrade.

Talk to your deployed agents

If you've built a chat.agent(), your coding assistant can hold a real conversation with it. list_agents shows what's registered in the current worker, and start_agent_chat, send_agent_message, and close_agent_chat drive a stateful session. Test an agent from Claude Code or Cursor without wiring up a UI first.


You: Start a chat with the support agent, ask it to look up order #4821
AI: I found order #4821. Placed March 15, shipped via FedEx (tracking
7891234). Current status: In Transit, estimated delivery March 19.
Tools used: lookupOrder, getShippingStatus

Manage prompt versions

AI Prompts are versioned, overridable config. The MCP server now manages them end to end. Use list_prompts and get_prompt_versions to see what's deployed, promote_prompt_version to ship a version, and create_prompt_override, update_prompt_override, remove_prompt_override, and reactivate_prompt_override to point an environment at a specific version without a redeploy. Iterate on a system prompt and roll it out from the same place you write the code.

Pull a health report with /report

get_report returns a server-rendered health report for an environment: a headline verdict plus text sparklines for whether work is flowing, whether the runs that start are healthy, and whether your telemetry is fresh. The verdict is computed server-side, so you get the same answer in chat, on the CLI, or over the API. In hosts that support MCP prompts, run /report health and it renders inline.

Also new since launch

  • Query your data with TRQL. query and get_query_schema run SQL-style queries over your runs, metrics, and llm_metrics tables. list_dashboards and run_dashboard_query pull the built-in dashboards.
  • Drive the dev server. start_dev_server, stop_dev_server, and dev_server_status run trigger dev in the background and stream its logs back.
  • Inspect deeper. get_span_details opens any span in a run trace, including the model, tokens, and cost on AI spans.
  • Switch profiles. whoami, list_profiles, and switch_profile move between accounts mid-session.
  • Safety flags. --readonly hides every write tool so the assistant can't change anything, and --dev-only scopes the server to your dev environment.

Get started

The MCP server always runs at @latest, so all of this is ready now:


npx trigger.dev@latest mcp --install

Read the MCP tools reference for the full list.

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