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aicayzer

bigquery-mcp

by aicayzer
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

BigQuery MCP Server

MCP server for secure BigQuery access across multiple Google Cloud projects.

Features

  • Multi-Project Access - Query across BigQuery projects with pattern matching

  • Advanced Analytics - Column analysis, data quality checks, schema exploration

  • Security Controls - SQL validation, query limits, read-only operations

  • CLI Configuration - Command-line arguments with config file fallback

  • Docker Support - Containerized deployment for easy integration

Related MCP server: bq-readonly-mcp

Documentation

Full documentation available at aicayzer.github.io/bigquery-mcp

Quick Start

Prerequisites

  • Python 3.11+

  • Google Cloud SDK

  • Docker (optional)

Authentication

gcloud auth application-default login

Installation

git clone https://github.com/aicayzer/bigquery-mcp.git
cd bigquery-mcp
pip install -r requirements.txt

MCP Client Setup

Claude Desktop

Add to ~/.config/claude/claude_desktop_config.json:

{
  "mcpServers": {
    "bigquery": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "--volume", "/Users/YOUR_USERNAME/.config/gcloud:/home/mcpuser/.config/gcloud:ro",
        "--volume", "/ABSOLUTE/PATH/TO/bigquery-mcp/logs:/app/logs",
        "bigquery-mcp:latest",
        "python", "src/server.py",
        "--project", "your-project:*",
        "--billing-project", "your-project"
      ]
    }
  }
}

Cursor IDE

Add to MCP settings:

{
  "bigquery": {
    "command": "docker",
    "args": [
      "run", "--rm", "-i",
      "--volume", "/Users/YOUR_USERNAME/.config/gcloud:/home/mcpuser/.config/gcloud:ro",
      "bigquery-mcp:latest",
      "python", "src/server.py",
      "--project", "your-project:*",
      "--billing-project", "your-project"
    ]
  }
}

Usage

CLI

# Single project
python src/server.py --project "your-project:*" --billing-project "your-project"

# Multiple projects with patterns
python src/server.py \
  --project "analytics-prod:user_*,session_*" \
  --project "logs-prod:application_*" \
  --billing-project "my-billing-project"

Docker

docker build -t bigquery-mcp .
docker run -v ~/.config/gcloud:/home/mcpuser/.config/gcloud:ro bigquery-mcp \
  python src/server.py --project "your-project:*" --billing-project "your-project"

Tools

  • list_projects() - List configured BigQuery projects

  • list_datasets(project) - List datasets in a project

  • list_tables(dataset, table_type) - List tables in a dataset

  • analyze_table(table) - Get table structure and statistics

  • analyze_columns(table, columns, sample_size) - Deep column analysis

  • execute_query(query, format, limit, timeout) - Execute SELECT queries

Configuration

CLI Arguments

python src/server.py \
  --project "analytics-prod:user_*,session_*" \
  --project "logs-prod:application_*" \
  --billing-project "my-billing-project" \
  --log-level INFO \
  --timeout 20 \
  --max-limit 50000

Config File (Optional)

bigquery:
  billing_project: "your-project"
  location: "EU"

projects:
  - project_id: "analytics-prod"
    datasets: ["user_*", "session_*"]
  - project_id: "logs-prod"  
    datasets: ["application_*"]

Contributing

  1. Fork the repository

  2. Create a feature branch from develop

  3. Make your changes with tests

  4. Submit a pull request to develop

License

MIT License - see LICENSE file.

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