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How to let Cursor or Claude Code write and run agent evals for you with Jevals

Install the Jevals MCP server so your coding agent can run and author evals.

Who it is forA developer who works in Cursor or Claude Code and wants evals added to an agent project without writing them by hand.

The problemWriting eval classes and questions from scratch is slow, and the eval code is easy to get wrong.

The outcomeYour coding agent creates eval definitions for your agent and runs them on sample traces from inside the editor.

What you need first

  • Python 3.10 or newer
  • An API key for one backend: AI_GATEWAY_API_KEY (Jev through Vercel AI Gateway), TYPESAFE_API_KEY, or OPENROUTER_API_KEY
  • A trace to evaluate: a messages list in the OpenAI chat format plus the tools you gave the model

Steps

  1. pip install "jevals[mcp]"
  2. export AI_GATEWAY_API_KEY=...
  3. Add the Jevals MCP server to the MCP settings of Cursor or Claude Code, following that client's documentation (inferred, check the README)
  4. Ask the coding agent to write evals for your agent's traces and run them with evaluate()

Prompt for your agent

Using the jevals MCP server, write an eval for <agent_repo> that checks whether the agent used its tool results. Run it on one trace from <traces_file>. Report the score and the trace id. Verify the eval runs without a syntax error before you report.

Caveat. The README does not say how to register the MCP server in each client, so check that client's setup before you assume it is connected.

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