• IDENTIFIED
  • ISOLATED
  • REDUCED
  • HUMAN

How to debug failed workflows with your AI

Connect Argo Workflows to your AI client to turn messy logs into clear failure reports. Once connected, your agent can scan your entire workflow history to find the needle in the haystack.

Ask AI about this page

Short answer

How do I find why my Argo workflow failed?

Your AI pulls the specific workflow instance data to identify the exact node and resource that hit an error. You get a direct breakdown of the failure point and the underlying cause.

Where every issue lands.

Debugging outcomes

The AI processes the workflow data to deliver these specific results.

IDENTIFIED

The failed node

The AI uses workflow data to name the specific step that crashed. You'll know exactly where the execution stopped.

ISOLATED

Resource errors

The agent identifies if the failure was due to a specific resource or container issue. This separates code bugs from infrastructure problems.

REDUCED

Log noise

Instead of scrolling through thousands of lines, your AI extracts only the relevant error messages. You get the signal without the noise.

HUMAN

Manual fixes

The AI points you to the broken code or config. You still handle the actual repair and redeployment of the workflow.

The workflow

What your AI does when a failure occurs.

The AI moves from broad visibility to specific error isolation.

  1. Scan history

    The AI looks through your recent Argo activity to find the specific failed instance you're asking about.

    list_workflows

  2. Fetch details

    Once the failed instance is found, the AI pulls the full state and status of that specific workflow.

    get_workflow

  3. Locate failure

    The AI parses the status of every node to find the one marked as failed.

    get_workflow

  4. Extract error

    The AI reads the error messages and resource constraints tied to that failed node.

    get_workflow

Try it

Copy these to start.

Use these prompts to begin debugging immediately.

Starting points

Replace the bracketed text with your actual workflow names or IDs.

Argo Workflows Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_XgODuKGP8hKPvAVimTmrdsOr5ag915WZ6oPDkNoq/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 — Argo Workflows capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "argo-workflows-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_XgODuKGP8hKPvAVimTmrdsOr5ag915WZ6oPDkNoq/mcp"
    }
  }
}
Copy into chat04

  • Find the most recent failed workflow in Argo and tell me which node caused it.

  • Look at workflow 'data-pipeline-prod' and explain why the 'transform' step failed.

  • List all failed workflows from the last hour and summarize their error messages.

  • Check the status of workflow 'cleanup-job-99' and tell me if it was a resource issue.

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

Start here

Connect Argo Workflows once, then ask.

Just follow the link to connect your account. Your credentials stay encrypted, and you can start asking questions in your preferred AI client immediately.

Connect Argo Workflows to your AI

FAQ

Common questions

  • 01

    Can the AI fix the code in my workflow?

    No. The AI identifies the error and the failed node, but you must perform the actual code changes and deployments.

  • 02

    Can the AI delete failed workflows?

    No. The available tools only allow the AI to list and get workflow data. It cannot modify or delete any Argo resources.

  • 03

    Does the AI see all my workflows?

    The AI can see any workflow that your connected Argo instance exposes through the list and get tools.

  • 04

    Can the AI trigger a retry of a failed node?

    No. The AI is limited to reading workflow data to help you debug. It cannot execute commands or trigger retries.

  • 05

    How does the AI know which node failed?

    It uses the data provided by the get_workflow tool to inspect the status of every node in the graph.

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

Connect Argo Workflows to Claude, Cursor, ChatGPT & more