BigQuery MCP Server

A Model Context Protocol (MCP) server for accessing Google BigQuery. This server enables Large Language Models (LLMs) to understand BigQuery dataset structures and execute SQL queries.

Features

Authentication and Connection Management

Supports Application Default Credentials (ADC) or service account key files
Configurable project ID and location settings
Authentication verification on startup

Tools

query
- Execute read-only (SELECT) BigQuery SQL queries
- Configurable maximum results and bytes billed
- Security checks to prevent non-SELECT queries
list_all_datasets
- List all datasets in the project
- Returns an array of dataset IDs
list_all_tables_with_dataset
- List all tables in a specific dataset with their schemas
- Requires a datasetId parameter
- Returns table IDs, schemas, time partitioning information, and descriptions
get_table_information
- Get table schema and sample data (up to 20 rows)
- Support for partitioned tables with partition filters
- Warnings for queries on partitioned tables without filters
dry_run_query
- Check query validity and estimate cost without execution
- Returns processing size and estimated cost

Security Features

Only SELECT queries are allowed (read-only access)
Default limit of 500GB for query processing to prevent excessive costs
Partition filter recommendations for partitioned tables
Secure handling of authentication credentials

Installation

Local Installation

# Clone the repository
git clone https://github.com/yourusername/bigquery-mcp-server.git
cd bigquery-mcp-server

# Install dependencies
bun install

# Build the server
bun run build

# Install command to your own path.
cp dist/bigquery-mcp-server /path/to/your_place

Docker Installation

You can also run the server in a Docker container:

# Build the Docker image
docker build -t bigquery-mcp-server .

# Run the container
docker run -it --rm \
  bigquery-mcp-server \
  --project-id=your-project-id

Or using Docker Compose:

# Edit docker-compose.yml to set your project ID and other options
# Then run:
docker-compose up

MCP Configuration

To use this server with an MCP-enabled LLM, add it to your MCP configuration:

{
  "mcpServers": {
    "BigQuery": {
      "command": "/path/to/dist/bigquery-mcp-server",
      "args": [
        "--project-id",
        "your-project-id",
        "--location",
        "asia-northeast1",
        "--max-results",
        "1000",
        "--max-bytes-billed",
        "500000000000"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/service-account-key.json"
      }
    }
  }
}

You can also use Application Default Credentials instead of a service account key file:

{
  "mcpServers": {
    "BigQuery": {
      "command": "/path/to/dist/bigquery-mcp-server",
      "args": [
        "--project-id",
        "your-project-id",
        "--location",
        "asia-northeast1",
        "--max-results",
        "1000",
        "--max-bytes-billed",
        "500000000000"
      ]
    }
  }
}

Setting up Application Default Credentials

To authenticate using Application Default Credentials:

Install the Google Cloud SDK if you haven't already:
# For macOS brew install --cask google-cloud-sdk # For other platforms, see: https://cloud.google.com/sdk/docs/install
Run the authentication command:
gcloud auth application-default login
Follow the prompts to log in with your Google account that has access to the BigQuery project.
The credentials will be saved to your local machine and automatically used by the BigQuery MCP server.

Testing

You can use inspector for testing and debugging.

npx @modelcontextprotocol/inspector dist/bigquery-mcp-server --project-id={{your_own_project}}

Usage

Using the Helper Script

The included run-server.sh script makes it easy to start the server with common configurations:

# Make the script executable
chmod +x run-server.sh

# Run with Application Default Credentials
./run-server.sh --project-id=your-project-id

# Run with a service account key file
./run-server.sh \
  --project-id=your-project-id \
  --location=asia-northeast1 \
  --key-file=/path/to/service-account-key.json \
  --max-results=1000 \
  --max-bytes-billed=500000000000

Manual Execution

You can also run the compiled binary directly:

# Run with Application Default Credentials
./dist/bigquery-mcp-server --project-id=your-project-id

# Run with a service account key file
./dist/bigquery-mcp-server \
  --project-id=your-project-id \
  --location=asia-northeast1 \
  --key-file=/path/to/service-account-key.json \
  --max-results=1000 \
  --max-bytes-billed=500000000000

Example Client

An example Node.js client is included in the examples directory:

# Make the example executable
chmod +x examples/sample-query.js

# Edit the example to set your project ID
# Then run it
cd examples
./sample-query.js

Command Line Options

--project-id: Google Cloud project ID (required)
--location: BigQuery location (default: asia-northeast1)
--key-file: Path to service account key file (optional)
--max-results: Maximum rows to return (default: 1000)
--max-bytes-billed: Maximum bytes to process (default: 500000000000, 500GB)

Required Permissions

The service account or user credentials should have one of the following:

roles/bigquery.user (recommended)

Or both of these:

roles/bigquery.dataViewer (for reading table data)
roles/bigquery.jobUser (for executing queries)

Example Usage

Query Tool

{
  "query": "SELECT * FROM `project.dataset.table` LIMIT 10",
  "maxResults": 100
}

List All Datasets Tool

// No parameters required

List All Tables With Dataset Tool

{
  "datasetId": "your_dataset"
}

Get Table Information Tool

{
  "datasetId": "your_dataset",
  "tableId": "your_table",
  "partition": "20250101"
}

Dry Run Query Tool

{
  "query": "SELECT * FROM `project.dataset.table` WHERE date = '2025-01-01'"
}

Error Handling

The server provides detailed error messages for:

Authentication failures
Permission issues
Invalid queries
Missing partition filters
Excessive data processing requests

Code Structure

The server is organized into the following structure:

src/
├── index.ts              # Entry point
├── server.ts             # BigQueryMcpServer class
├── types.ts              # Type definitions
├── tools/                # Tool implementations
│   ├── query.ts          # query tool
│   ├── list-datasets.ts  # list_all_datasets tool
│   ├── list-tables.ts    # list_all_tables_with_dataset tool
│   ├── table-info.ts     # get_table_information tool
│   └── dry-run.ts        # dry_run_query tool
└── utils/                # Utility functions
    ├── args-parser.ts    # Command line argument parser
    └── query-utils.ts    # Query validation and response formatting

License

MIT

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

A Model Context Protocol server that enables LLMs to understand BigQuery dataset structures and execute SQL queries.

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