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How to let a coding agent query and edit your Tracely workspace with Tracely AI

Connect a coding agent to the Tracely MCP endpoint with an ingest key.

Credentials. The ingest key gives the connected agent access to your workspace, so use a key scoped for development and rotate it if it leaks.

Who it is forA developer who uses a coding agent day to day and wants it to inspect failing traces and set up cases without leaving the editor.

The problemSwitching between the editor and the Tracely UI slows down debugging of agent failures.

The outcomeA coding agent reads traces, creates evaluators, cases and alerts in your workspace through the MCP endpoint.

What you need first

  • Docker and Docker Compose
  • For local development: uv, Node 20+ and pnpm
  • A GitHub repository with pull requests, if you want the CI gate
  • Python, to install the tracelyai-sdk package

Steps

  1. Run docker compose --profile demo up -d --build --wait to start a local Tracely instance.
  2. Note the ingest key from the seeded project, which the README lists as tracely_dev_key for local use.
  3. Add the MCP endpoint at http://localhost:8000/mcp to your coding agent's MCP settings with that key.
  4. Ask the agent to list recent failing traces and summarize them.
  5. Review anything the agent creates in the Tracely UI before relying on it.

Prompt for your agent

Using the Tracely-ai repository running locally at http://localhost:8000, connect to the MCP endpoint at /mcp with the ingest key <ingest-key>. List the five most recent failing traces and report their agent names and failure reasons. Verify that the list matches what the traces view shows at http://localhost:3001.

Caveat. The README says the MCP endpoint uses an ordinary ingest key, but the exact client configuration for each coding agent is not in the README and must be set up by you.

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