AI Delivery MCP

AI Delivery MCP exposes tools for automating task delivery:

• run_task_delivery

• create_merge_request

• update_jira

• generate_release_note

The recommended first path is run_task_delivery in dry-run mode. It validates the workflow shape without creating GitLab or Jira side effects.

Setup

npm install
cp .env.example .env
npm test
npm run build

Related MCP server: Google Jules MCP

Environment

See .env.example for GitLab, Jira, release note, and evidence settings.

Dry-Run Verification

npm run build
DELIVERY_DRY_RUN=true npm run smoke:dry-run

Expected output includes:

{
  "status": "dry_run",
  "evidencePath": "artifacts/delivery-evidence/<timestamp>-DRY-123.json"
}

The evidence JSON includes the merge request preview payload, Jira dry-run result, release note markdown, and step-by-step execution status.

MCP Usage

Build the server:

npm run build

Run with stdio:

node dist/src/index.js

Configure your MCP client to launch node /absolute/path/to/dist/src/index.js with the needed environment variables.

Real Integration Verification

Use a test GitLab project and a test Jira issue first. Run run_task_delivery with dryRun: false, then verify:

• GitLab MR title, description, reviewers, labels, or metadata.

• Jira comment or transition.

• Release note content and evidence JSON.

Definition of Done Evidence

For dry-run verification:

• MR preview payload is returned by run_task_delivery.

• Jira comment preview is included in the delivery result.

• Release note markdown is generated from branch and ticket context.

• Evidence JSON is written under artifacts/delivery-evidence.

For real verification:

• Use a test GitLab branch and test Jira issue.

• Run run_task_delivery with dryRun: false.

• Capture the GitLab MR URL, Jira comment or transition evidence, and generated release note path.