- SYNTAX
- RESOURCES
- DATA
- HUMAN
Short answer
How can I use AI to fix my BigQuery errors?
Your AI uses BigQuery job data to pinpoint the exact cause of a failure. It pulls error messages and examines recent job history to suggest fixes. You get a clear path to resolving the issue.
Investigation outcomes
Where your debugging efforts land.
The AI categorizes findings based on the nature of the failure.
SYNTAX
SQL errors found
The AI identifies typos or invalid functions in your query. You get the corrected SQL string immediately.
RESOURCES
Quota and limits
The AI checks if you hit memory or slot limits. It explains which resource caused the job to crash.
DATA
Schema mismatches
The AI detects when a column type or table name doesn't match your query. It points to the specific table causing the conflict.
HUMAN
Manual intervention
The AI flags issues it cannot fix, like permission errors or missing datasets. You'll need to handle these in the Google Cloud Console.
The workflow
What your AI does when a job fails.
The AI automates the investigation process by pulling real-time job data.
Identify failed jobs
The AI scans your recent activity to find the specific execution that didn't complete.
list_jobsFetch error details
It pulls the specific error trace and status for the problematic execution.
get_jobAnalyze the query
The AI looks at the exact SQL that was run to find logic or syntax flaws.
get_jobTest a fix
Once a solution is found, the AI can run a new version of the query to verify it works.
execute_query
Try it
Copy these to start.
Use these prompts to kick off an investigation.
Starting points
These are starting points. Swap out the job IDs or table names with your own.
Google BigQuery Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_XL1CHYzMkCvLxlGLPBzLHDOTg35sqGtg0BPtLGTY/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 — Google BigQuery capabilities are ready to use.
{
"mcpServers": {
"google-bigquery-mcp": {
"url": "https://edge.vinkius.com/vk_preview_XL1CHYzMkCvLxlGLPBzLHDOTg35sqGtg0BPtLGTY/mcp"
}
}
}Find the error message for my last failed BigQuery job.
Look at the job with ID 'job_abc123' and tell me why it failed.
Check my recent job history and list any failures from the last hour.
Run this corrected SQL query and tell me if it succeeds: SELECT * FROM my_dataset.my_table
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Google BigQuery once, then ask.
One connection gives your AI access to your BigQuery environment. Your credentials stay encrypted and secure on our side.
Connect Google BigQuery to your AIFAQ
Common questions
- 01
Can the AI fix my permissions?
No. The AI can only read job data and run queries. It cannot change IAM roles or project permissions.
- 02
Can the AI delete my tables?
No. This MCP does not have tools to delete data or drop tables.
- 03
Does the AI see all my data?
The AI only sees the data it needs to execute the queries you ask it to run or to inspect job details.
- 04
Can it run queries automatically?
It can run queries when you explicitly ask it to via a prompt.
- 05
Will it cost me money to connect?
Connecting the MCP is handled through Vinkius, but BigQuery execution costs are billed by Google Cloud as usual.
More questions about Google BigQuery? The Connector page answers them. See everything the Google BigQuery Connector can do
Connect Google BigQuery to Claude, Cursor, ChatGPT & more
