• TRENDS
  • FAILURE
  • HISTORY
  • HUMAN

How to analyze test run results with your AI

Connect BugBug to your agent to turn raw test logs into actionable quality insights. Your AI handles the data gathering so you can focus on fixing the bugs.

Ask AI about this page

Short answer

How can I use AI to analyze my BugBug test results?

Your agent uses the connector to pull specific run data and historical suite results. It then identifies patterns in failures or specific regression trends for you. You get a clear picture of your software quality without digging through logs manually.

Where every insight lands.

The outcomes of your analysis

Once your agent has access to your BugBug data, it organizes findings into these categories.

TRENDS

Quality trend reports

The AI looks at multiple runs to see if specific features are getting more unstable. You get a summary of whether your quality is improving or slipping.

FAILURE

Root cause identification

The agent pulls data from specific failed runs to find the exact point of failure. It highlights the error messages and context needed to start a fix.

HISTORY

Historical regression checks

By comparing current results against previous ones, the AI flags new regressions. It tells you exactly what changed between a passing and a failing state.

HUMAN

Manual triage required

The AI flags complex failures that don't match known patterns. These are the cases where you need to step in and investigate the application state yourself.

The workflow

What your AI does when the data arrives.

The agent follows a logical path from fetching raw data to presenting you with a summary of the health of your tests.

  1. Fetch run history

    The agent starts by gathering a list of recent test executions to establish a baseline.

    list_test_runs

  2. Target specific suites

    It narrows the scope by looking at the history of specific test suites to find relevant patterns.

    list_suite_runs

  3. Extract failure details

    The agent pulls the granular data from a specific execution to see exactly what went wrong.

    get_test_run

  4. Synthesize findings

    The agent compares the gathered data points to identify if a failure is a one-off or a recurring trend.

    list_test_runs

Try it

Copy these to start.

Use these prompts to kick off your analysis immediately.

Starting points

These are just ideas. Swap out the suite names or run IDs with your actual BugBug data.

BugBug Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_Na0MiOd5DLIkm5F48FVbS0nJAKsJ9lCI3JIUBfdX/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 — BugBug capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "bugbug-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_Na0MiOd5DLIkm5F48FVbS0nJAKsJ9lCI3JIUBfdX/mcp"
    }
  }
}
Copy into chat04

  • Look at the last five test runs in BugBug and tell me if the failure rate is increasing.

  • Pull the results for the 'Checkout Flow' suite and identify the most common error message.

  • Check the most recent test run and summarize why the login step failed.

  • Compare the results of the last three suite runs to see if we have a regression in the dashboard module.

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

Start here

Connect BugBug once, then ask.

Just link your account once. Your credentials stay encrypted, and you can immediately start asking questions about your test data in your preferred AI client.

Connect BugBug to your AI

FAQ

How the analysis works

  • 01

    Can the AI fix the broken tests for me?

    No. The AI can identify why a test failed and suggest what might be wrong, but you have to go into your code or BugBug to actually apply the fix.

  • 02

    Does the AI delete any of my test runs?

    No. The AI only has read access to your test data. It cannot delete, modify, or create new test runs in BugBug.

  • 03

    Can I ask about a specific test run ID?

    Yes. Once connected, you can provide a specific run ID and the AI will pull that data to analyze it.

  • 04

    How does the AI know which suite to look at?

    You tell it. You can name a specific suite or ask it to look at all recent runs to find what it needs.

  • 05

    Will my BugBug login details be shared with the AI model?

    No. Vinkius manages the connection securely. Your AI client only sees the data returned by the tools, not your login credentials.

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

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