- LOG ACCESS
- JOB SCOPE
- ROOT CAUSE
- HUMAN ACTION
Short answer
How can I debug failed builds using my AI?
Your agent uses Travis CI tools to fetch specific build logs and job details. It identifies the exact error causing a failure so you can fix it immediately. You get a clear breakdown of what went wrong below.
Where the data lands.
What you get from your agent
The AI handles the data retrieval so you can focus on the fix.
LOG ACCESS
Direct error visibility
The agent pulls the specific logs from a failed build. You see the stack trace and error messages without leaving your chat.
JOB SCOPE
Identify failing jobs
Your agent lists all jobs within a build to pinpoint exactly which step failed. This narrows down the search area instantly.
ROOT CAUSE
Automated error analysis
The AI reads the raw log data to find the culprit. It interprets the failure and explains the issue in plain English.
HUMAN ACTION
Code fixes required
The AI identifies the problem but cannot rewrite your repository. You take the findings and apply the fix to your code.
The workflow
What your AI does when a build fails.
The agent acts as a bridge between your CI environment and your development chat.
Locate the failure
The agent scans your recent activity to find the specific build that didn't pass.
list_build_jobsFetch the logs
Once the failed job is identified, the agent pulls the full output for that specific run.
get_build_detailsParse the error
The agent reads through the log text to find the exit code or the specific exception.
get_build_detailsReport the issue
The agent presents a summary of the failure, including the file and line number involved.
get_build_details
Try it
Copy these to start.
Use these prompts to kick off the debugging process.
Starting points
Replace the bracketed text with your actual build or job IDs.
Travis CI Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_Tsr2nXTZjqLuHF648kXSBd1jz2jny42wR3IGL8IB/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Travis CI capabilities are ready to use.
{
"mcpServers": {
"travis-ci-mcp": {
"url": "https://edge.vinkius.com/vk_preview_Tsr2nXTZjqLuHF648kXSBd1jz2jny42wR3IGL8IB/mcp"
}
}
}List the most recent build jobs for my project to see what failed.
Get the details for build #12345 and tell me why it failed.
Check the logs for the 'test' job in my last Travis CI run.
Summarize the error found in the logs for build ID 98765.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Travis CI once, then ask.
One click connects your account. Your credentials stay encrypted and secure, and you can start debugging immediately.
Connect Travis CI to your AIFAQ
How the Travis CI MCP behaves
- 01
Can the AI fix my code automatically?
No. The AI reads the logs and tells you what is wrong, but you must manually apply the code changes.
- 02
Can the AI trigger a new build?
No. The current tools only allow the agent to read build details and job lists.
- 03
Does the AI have access to my source code?
No. The agent only sees the build logs and job metadata provided by Travis CI.
- 04
Can I use this with any AI client?
Yes, as long as the client is MCP-compatible, like Claude, Cursor, or Windsurf.
- 05
Will my Travis CI credentials be shared with the AI model?
No. Vinkius manages the connection securely so your credentials stay between the MCP and Travis CI.
More questions about Travis CI? The Connector page answers them. See everything the Travis CI Connector can do
Connect Travis CI to Claude, Cursor, ChatGPT & more
