• EXECUTION
  • MONITORING
  • DISCOVERY
  • HUMAN

How to trigger and monitor deployments with your AI

Connect Harness to your AI client once. From there, you can manage your deployment lifecycle using plain text.

Ask AI about this page

Short answer

Can I run and track deployments with my AI?

Yes. You can command your AI to start specific pipelines and check their live status. You'll see exactly how the following process works.

Deployment outcomes

What you get

These are the results of your commands.

EXECUTION

Active pipelines

Your AI starts the exact deployment you requested. You get immediate confirmation that the process is running.

MONITORING

Live status updates

The AI pulls the current state of a job. You'll know if a deployment succeeded or failed.

DISCOVERY

Pipeline visibility

Your AI finds all available deployment paths. You can ask what's available before you trigger anything.

HUMAN

Manual intervention

The AI cannot fix broken code or change pipeline logic. You still handle the actual debugging and configuration.

The workflow

What your AI does when the command arrives.

The AI acts as the bridge between your text and the Harness engine.

  1. Find pipelines

    The AI looks through your available deployment paths to identify the one you want to run.

    list_pipelines

  2. Start deployment

    Once identified, the AI sends the command to launch the specific production workflow.

    execute_pipeline

  3. Check progress

    The AI queries the system to see if the deployment is still moving or if it hit a snag.

    get_execution_status

  4. Report status

    The AI pulls the latest execution data to tell you if the job is finished.

    get_execution_status

Try it

Copy these to start.

Use these prompts to begin interacting with Harness.

Starting points

These are opening lines. Swap out the names for your actual pipeline or environment names.

Harness Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_FKVrjuS3OzI8VzOXfjNk3FkTG4tKnGJtdNAAcY8J/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Harness capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "harness-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_FKVrjuS3OzI8VzOXfjNk3FkTG4tKnGJtdNAAcY8J/mcp"
    }
  }
}
Copy into chat04

  • List all my available deployment pipelines.

  • Run the production-deploy pipeline now.

  • What is the current status of the last deployment?

  • Check if the web-app-service pipeline finished successfully.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Harness once, then ask.

One link connects your account. Your login stays encrypted on our side, and you can start using these commands immediately.

Connect Harness to your AI

FAQ

How this task behaves

  • 01

    Can the AI create new pipelines?

    No. The AI can only list, start, and monitor existing pipelines.

  • 02

    Can the AI fix a failed deployment?

    No. The AI can tell you that a deployment failed, but you must handle the actual fix yourself.

  • 03

    Does the AI need my Harness password?

    No. Vinkius manages the connection so you don't have to share credentials with the AI.

  • 04

    Can the AI stop a running pipeline?

    No. The current tools only allow for starting and checking the status of pipelines.

  • 05

    How does the AI know which pipelines exist?

    It uses the list tool to see every pipeline registered in your Harness account.

  • More questions about Harness? See everything the Harness Connector can do

Connect Harness to Claude, Cursor, ChatGPT & more