MCP

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Common workflows

• Implement from executable specs. Use momentic-spec before changing user-visible behavior so the affected Momentic tests capture the intended product behavior and validate the finished implementation.
• Author and extend coverage. Use momentic-test to create tests, steps, and modules against a live browser. Use momentic-mobile-test for Android and iOS.
• Understand a branch failure. Use momentic-maintain to find runs for the branch, inspect the saved classifications and run evidence, and identify the earliest point where behavior diverged.
• Investigate failures on main. DevX and on-call engineers can group recent failures by status or classification, inspect representative runs, and distinguish application regressions from test, environment, and Momentic issues.
• Deflake tests and reduce latency. Find quarantined, recovered, and retry-heavy runs, then repair unstable tests and reduce time spent in failure recovery. Branch, classification, and minimum-attempt filters help prioritize repeated failure patterns.

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Prerequisites

• Momentic CLI installed locally (MCP runs on your machine)
• A project with a valid momentic.config.yaml
• A MOMENTIC_API_KEY available to the MCP process (most editors do not inherit your shell environment)

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Setup instructions

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General

npx momentic mcp --config /absolute/path/to/momentic.config.yaml

• momentic-test: how to build reliable tests, steps, and modules
• momentic-spec: how to write affected tests before product changes
• momentic-maintain: how to investigate branch and main failures, audit classifications, deflake quarantined or recovered tests, reduce retries, and repair durable test issues

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Claude Code

claude mcp add --transport stdio momentic -- npx momentic mcp --config /absolute/path/to/momentic.config.yaml

claude mcp add --transport stdio momentic -- cmd /c npx momentic mcp --config C:\path\to\momentic.config.yaml

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Codex

codex mcp add momentic -- npx momentic mcp --config /absolute/path/to/momentic.config.yaml

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Cursor

{
  "mcpServers": {
    "momentic": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "momentic",
        "mcp",
        "--config",
        "/absolute/path/to/momentic.config.yaml"
      ],
      "env": { "MOMENTIC_API_KEY": "your-api-key" }
    }
  }
}

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Devin

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OpenCode

{
  "mcp": {
    "momentic": {
      "type": "local",
      "command": [
        "npx",
        "momentic",
        "mcp",
        "--config",
        "/absolute/path/to/momentic.config.yaml"
      ],
      "environment": { "MOMENTIC_API_KEY": "your-api-key" },
      "enabled": true
    }
  }
}

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VS Code (Copilot)

npx momentic mcp --config /absolute/path/to/momentic.config.yaml

"momentic": {
  "env": { "MOMENTIC_API_KEY": "your-api-key" }
}

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Other clients

• Command: npx
• Arguments: momentic mcp --config /absolute/path/to/momentic.config.yaml
• Env: MOMENTIC_API_KEY=your-api-key

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Install skills

npx skills add momentic-ai/skills

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Invoke the skill

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Authorship

/momentic-test write a test for the checkout flow

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Maintenance

/momentic-maintain investigate and repair run <run-id>

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Spec-driven development

/momentic-spec add a confirmation message after a file is attached

## Momentic spec-driven development

Use the `momentic-spec` skill before implementing user-visible product changes.
It captures the intended behavior in the smallest affected set of Momentic
tests, then validates the implementation at durable UI checkpoints. Follow the
skill's workflow for test data, disabled specifications, and verification.

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Usage tips

• Model: use the newest model your editor offers. High reasoning gives the best results; Medium is about 20% faster with some quality loss.
• Invoke the relevant skill explicitly when authoring, maintaining, or changing product behavior.
• Be specific in prompts. For exploratory runs, include a step limit.
• Let sessions terminate: the agent calls momentic_session_terminate to close the browser. Hard-stopping your editor leaks browser processes.
• Gitignore .momentic-mcp/. MCP stores screenshots, videos, and traces there.
• Long-running steps: momentic_run_step returns within 30 seconds. If the step range hasn’t finished, it returns a stepRunnerId that you can poll with momentic_poll_runner. Pass an optional timeoutSeconds (0-30, default 0) to hold the poll open briefly instead of busy-polling.

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Related

• What is AI-native testing?