• MAP
  • ISOLATE
  • VALIDATE
  • HUMAN

How to perform root cause analysis with your AI

Connect your AI to your system data. It will trace failures through actual causal chains instead of guessing based on error messages.

Ask AI about this page

Short answer

How can I use AI to find the real cause of a failure?

Your AI maps the mechanistic dependencies between components to find the true trigger. This moves you from chasing symptoms to identifying the specific point where the logic or state broke. You get a clear map of the failure path.

The investigation outcomes.

Where the analysis leads.

The AI processes your system data to produce these specific results.

MAP

Dependency maps

The AI builds a logical graph of how components interact. You see exactly which service or function sits upstream from the failure.

ISOLATE

Trigger identification

The AI pinpoints the specific state change that started the cascade. It separates the actual cause from the resulting noise.

VALIDATE

Hypothesis testing

You can propose a theory about why something broke. The AI checks the causal links to see if that theory holds up against the data.

HUMAN

Decision support

The AI provides the evidence, but you decide on the fix. It hands you the logic so you can confidently deploy a patch or rollback.

The workflow

What your AI does when a failure arrives.

The AI acts as a forensic investigator, following the breadcrumbs through your architecture.

  1. Trace the error

    The AI looks at the error logs and identifies the immediate downstream effects.

    validate_causal

  2. Map dependencies

    It builds a model of the system to see how the error traveled through different layers.

    validate_causal

  3. Verify the trigger

    The AI tests the relationship between the suspected cause and the observed symptom.

    validate_causal

  4. Confirm the path

    It runs a final check to ensure no other hidden dependencies could have caused the same result.

    validate_causal

Try it

Copy these to start.

Use these prompts to kick off an investigation.

Starting points

Replace the bracketed text with your specific log files, service names, or error traces.

Causal-Graph Navigator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_RSNSq5Bfgj6GuLz5Lhoemr4vjWdu41Ndxa0ZeYxu/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 — Causal-Graph Navigator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "causal-graph-navigator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_RSNSq5Bfgj6GuLz5Lhoemr4vjWdu41Ndxa0ZeYxu/mcp"
    }
  }
}
Copy into chat04

  • Analyze the error in this log file from the auth-service and find the causal trigger.

  • Map the dependencies for the database timeout reported in this trace.

  • I think the recent deployment in the checkout-api caused this latency. Validate this hypothesis.

  • Trace the failure from the frontend timeout back to the original system component.

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

Start here

Connect Causal-Graph Navigator once, then ask.

One connection to your preferred AI client is all it takes. Your credentials stay encrypted and the setup is handled on our end.

Connect Causal-Graph Navigator to your AI

FAQ

How the analysis behaves

  • 01

    Can the AI fix the code for me?

    No. The AI identifies the cause and provides the evidence, but you must perform the actual code changes or system repairs.

  • 02

    Does the AI delete my logs?

    No. The AI only reads the data provided to perform the analysis. It has no permission to delete or modify your logs.

  • 03

    Can it analyze real-time traffic?

    It analyzes the data you provide through the connection, such as logs or traces, to build its causal model.

  • 04

    Will it suggest a fix?

    It can suggest a logical path based on the causal map, but it cannot execute commands on your infrastructure.

  • 05

    How does it know which cause is real?

    It uses the validate_causal tool to check the mechanistic links between events, ensuring it follows a logical chain rather than just correlation.

  • More questions about Causal-Graph Navigator? The Connector page answers them. See everything the Causal-Graph Navigator Connector can do

Connect Causal-Graph Navigator to Claude, Cursor, ChatGPT & more