• ERROR
  • STATUS
  • CONTEXT
  • HUMAN

How to debug failed pipelines with your AI

Connect Harness to your AI client once. From then on, your agent can inspect deployment logs and execution data to find errors for you.

Ask AI about this page

Short answer

How can I use AI to find why my pipeline failed?

Your AI pulls execution statuses and step-level details from Harness to find the exact cause of a failure. You get a clear breakdown of the error and the context needed to fix it.

Debugging outcomes

Where your error data lands.

The AI categorizes every failure into actionable outcomes.

ERROR

Root cause identified

The AI finds the specific step that crashed. You get the error message and the reason the deployment stopped.

STATUS

Current state check

Your agent pulls the latest execution status. You'll know if a pipeline is still running, stuck, or finished.

CONTEXT

Pipeline structure mapped

The AI looks at the full pipeline definition. This helps it understand how the failed step relates to the rest of your workflow.

HUMAN

Manual intervention needed

If the error is a logic flaw or a missing credential, the AI flags it for you. You decide how to fix the code or settings.

The workflow

What your AI does when a failure occurs.

The AI moves from high-level status checks to deep-dive error analysis.

  1. Check recent runs

    The AI looks for the most recent deployment attempts to find the one that failed.

    list_executions

  2. Verify the failure

    It pulls the specific status of the failed run to confirm it didn't just time out.

    get_execution_status

  3. Analyze the pipeline

    The agent examines the pipeline structure to understand the sequence of steps.

    get_pipeline

  4. Pinpoint the error

    The AI correlates the failed status with the specific step details to tell you what went wrong.

    get_execution_status

Try it

Copy these to start.

Paste these into your chat to begin debugging.

Starting points

Replace the bracketed text with your specific Harness identifiers like pipeline names or execution IDs.

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

  • Check the status of the last execution for the 'production-deploy' pipeline.

  • Why did the execution 'exec-12345' in my 'frontend-ci' pipeline fail?

  • List all recent executions for the 'data-sync' pipeline to see if they are succeeding.

  • Look at the 'main-api' pipeline and tell me which step failed in the most recent run.

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

Start here

Connect Harness once, then ask.

You only need to link your account once. Your credentials stay encrypted, and you can immediately start asking your AI about your deployments.

Connect Harness to your AI

FAQ

How the debugging task behaves

  • 01

    Can the AI fix the failed pipeline for me?

    No. The AI can only read execution statuses and pipeline details to tell you what happened. You must manually apply the fix.

  • 02

    Does the AI see my secret credentials?

    No. The AI only accesses the execution data and pipeline configurations provided by the tools.

  • 03

    Can I ask the AI to trigger a new deployment?

    No. The current tools only allow the AI to read status and pipeline information, not to execute or start new runs.

  • 04

    How does the AI know which pipeline to look at?

    You tell the AI the name of the pipeline in your prompt, and it uses that information to find the right data.

  • 05

    Can the AI delete a failed execution?

    No. There are no tools available to modify or delete execution history.

  • More questions about Harness? The Connector page answers them. See everything the Harness Connector can do

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