BigQuery MCP server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@BigQuery MCP serverlist all tables in my dataset"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
BigQuery MCP server
A Model Context Protocol server that provides access to BigQuery. This server enables LLMs to inspect database schemas and execute queries.
Components
Tools
The server implements one tool:
execute-query: Executes a SQL query using BigQuery dialectlist-tables: Lists all tables in the BigQuery databasedescribe-table: Describes the schema of a specific table
Related MCP server: Google Cloud MCP Server
Configuration
The server can be configured either with command line arguments or environment variables.
Argument | Environment Variable | Required | Description |
|
| Yes | The GCP project ID. |
|
| Yes | The GCP location (e.g. |
|
| No | Only take specific BigQuery datasets into consideration. Several datasets can be specified by repeating the argument (e.g. |
|
| No | Path to a service account key file for BigQuery. If not provided, the server will use the default credentials. |
Quickstart
Install
Installing via Smithery
To install BigQuery Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install mcp-server-bigquery --client claudeClaude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development/Unpublished Servers Configuration
"mcpServers": {
"bigquery": {
"command": "uv",
"args": [
"--directory",
"{{PATH_TO_REPO}}",
"run",
"mcp-server-bigquery",
"--project",
"{{GCP_PROJECT_ID}}",
"--location",
"{{GCP_LOCATION}}"
]
}
}Published Servers Configuration
"mcpServers": {
"bigquery": {
"command": "uvx",
"args": [
"mcp-server-bigquery",
"--project",
"{{GCP_PROJECT_ID}}",
"--location",
"{{GCP_LOCATION}}"
]
}
}Replace {{PATH_TO_REPO}}, {{GCP_PROJECT_ID}}, and {{GCP_LOCATION}} with the appropriate values.
Development
Building and Publishing
To prepare the package for distribution:
Increase the version number in
pyproject.tomlSync dependencies and update lockfile:
uv syncBuild package distributions:
uv buildThis will create source and wheel distributions in the dist/ directory.
Publish to PyPI:
uv publishNote: You'll need to set PyPI credentials via environment variables or command flags:
Token:
--tokenorUV_PUBLISH_TOKENOr username/password:
--username/UV_PUBLISH_USERNAMEand--password/UV_PUBLISH_PASSWORD
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
npx @modelcontextprotocol/inspector uv --directory {{PATH_TO_REPO}} run mcp-server-bigqueryUpon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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