Confident AI MCP

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Confident AI's official MCP server, connecting AI tools to the platform behind DeepEval for evaluating, observing, and iterating on LLM quality. Agents can trigger and read evaluation runs, inspect metric scores and failing test cases, manage golden datasets, and review production traces to close the loop between eval results and code changes.

Connect

Add this configuration to .claude/mcp.json

{
  "mcpServers": {
    "confident-ai": {
      "command": "npx",
      "args": [],
      "env": {
        "CONFIDENT_API_KEY": "<YOUR_CONFIDENT_API_KEY>"
      }
    }
  }
}

Tools (3)

list_test_runs

List evaluation test runs and their aggregate metric scores.

{
  "type": "object",
  "properties": {
    "limit": {
      "type": "integer",
      "description": "Maximum number of test runs to return"
    }
  }
}

get_failing_test_cases

Retrieve failing test cases for a test run, including metric reasons.

{
  "type": "object",
  "required": [
    "test_run_id"
  ],
  "properties": {
    "test_run_id": {
      "type": "string",
      "description": "Identifier of the test run"
    }
  }
}

list_datasets

List golden datasets available in the workspace.

{
  "type": "object",
  "properties": {}
}

Resources

This server does not expose any resources.

Prompts

This server does not expose any prompts.

Server information

Author
Confident AI (@confident-ai)
Repository
https://github.com/confident-ai/confident-mcp-server
License
Apache-2.0
Stars
0
Last updated
August 3, 2026