Gcp Bq Data Export
Helps with Google Cloud, data as part of deploying and managing cloud infrastructure workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add gcp-bq-data-export npx -- -y @trustedskills/gcp-bq-data-export
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"gcp-bq-data-export": {
"command": "npx",
"args": [
"-y",
"@trustedskills/gcp-bq-data-export"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill allows AI agents to export data from Google BigQuery tables. It can specify the table, destination (e.g., Cloud Storage bucket), and file format for exporting data. The exported data can then be used for analysis, reporting, or integration with other systems.
When to use it
- You need to extract a subset of data from a large BigQuery table for further processing.
- You want to create backups of your BigQuery tables in a different format (e.g., CSV, JSON).
- You're building a data pipeline that requires data from BigQuery as input.
- You need to share BigQuery data with users or systems that don’t have direct access to BigQuery.
Key capabilities
- Specifies the source BigQuery table for export.
- Defines the destination Cloud Storage bucket and path.
- Supports various file formats (e.g., CSV, JSON).
Example prompts
- "Export the 'orders' table from my BigQuery dataset to a CSV file in my Cloud Storage bucket."
- "Can you export all data from the
sales_datatable into a JSON file?" - “Please extract the ‘customer_transactions’ table and save it as a backup in Cloud Storage.”
Tips & gotchas
- Ensure your AI agent has appropriate permissions to access both BigQuery and Cloud Storage.
- Large datasets may take considerable time to export, so consider using filtering or partitioning for efficiency.
Tags
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| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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Passed automated security scans.