- ANALYSIS
- INVESTIGATION
- RECOVERY
- HUMAN
Short answer
How can my AI help me fix Zeabur deployment errors?
Your AI pulls the specific build logs from Zeabur and uses shell commands to investigate the environment or test fixes. You get a direct path from a failed build to a working deployment through automated log parsing and command execution.
The debugging outcomes.
Where your troubleshooting lands.
The AI moves through the failure lifecycle, from reading logs to proposing fixes.
ANALYSIS
Root cause identified
The AI reads your Zeabur build logs to find the exact line where the process crashed. You get a clear explanation of the error.
INVESTIGATION
Environment verified
Your agent runs shell commands to check files or environment variables. This confirms if the issue is code-based or configuration-based.
RECOVERY
Fixes proposed
The AI suggests specific changes to your code or config files. You decide which ones to apply to get the build passing.
HUMAN
Manual intervention
If the error is a platform outage or a billing issue, the AI tells you exactly what to check in the Zeabur dashboard.
The workflow
What your AI does when a build fails.
The AI takes over the tedious parts of troubleshooting so you don't have to scroll through thousands of lines of text.
Fetch logs
The AI pulls the raw output from your failed Zeabur build to see what went wrong.
get_build_logsInspect files
It pulls specific configuration or source files to check for syntax errors or missing dependencies.
download_fileTest fixes
Your agent runs commands in the environment to verify that a proposed change actually works.
execute_commandVerify state
The AI checks the current directory or environment state to ensure the fix is ready for deployment.
execute_command
Try it
Copy these to start.
Use these prompts to kick off the debugging process.
Starting points
These are opening lines. Swap out the specific project names or build IDs for your own.
Zeabur Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_C259WqFoZVL0U3fl3UAYmeTpTKhOp70hGTqhzXJ5/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 — Zeabur capabilities are ready to use.
{
"mcpServers": {
"zeabur-paas-deployment-mcp": {
"url": "https://edge.vinkius.com/vk_preview_C259WqFoZVL0U3fl3UAYmeTpTKhOp70hGTqhzXJ5/mcp"
}
}
}Pull the logs for my last failed Zeabur build and tell me why it crashed.
Download the config file for my 'api-service' project and check for typos.
Run a shell command to check the version of Node.js in my current Zeabur environment.
Look at the build logs for project 'frontend-app' and suggest a fix for the dependency error.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Zeabur once, then ask.
One connection gives your AI access to your deployment data. Your credentials stay encrypted and secure on our side.
Connect Zeabur to your AIFAQ
How this task behaves
- 01
Can the AI fix my deployment automatically?
No. The AI can suggest fixes and run commands to test them, but you must ultimately approve or trigger the final deployment.
- 02
Can the AI delete my Zeabur projects?
No. The available tools only allow for reading logs, downloading files, and executing commands. It cannot delete resources.
- 03
Does the AI need my Zeabur password?
No. You connect via the Vinkius platform, which manages the connection securely without exposing your password to the AI.
- 04
Can the AI see my entire codebase?
The AI can only see the files it specifically downloads or the logs it pulls via the provided tools.
- 05
What happens if a shell command fails?
The AI receives the error output from the command and uses it to refine its next troubleshooting step.
More questions about Zeabur? See everything the Zeabur Connector can do
Connect Zeabur to Claude, Cursor, ChatGPT & more
