Prepare the server locally
Run this once before adding it to Claude Code.
git clone https://github.com/codearranger/mcp-server-bigquery
cd mcp-server-bigqueryThen follow the repository README for any remaining dependency or build steps.
Register it in Claude Code
claude mcp add -e "--project=${--project}" -e "--location=${--location}" bigquery -- uvx mcp-server-bigquery --project YOUR_PROJECT_ID --location YOUR_LOCATIONReplace any placeholder paths in the command with the real path on your machine.
--project--location+ 2 optionalMake your agent remember this setup
bigquery's config, env vars, and the gotchas you hit — recalled in every future Claude Code, Cursor, and Codex session.
npx conare@latestFree · one command · indexes the sessions already on disk. Set up in the browser instead →
What it does
- Inspect BigQuery database schemas
- List all tables within a project or dataset
- Execute custom SQL queries using BigQuery dialect
- Support for service account authentication
- Filterable dataset access
Tools 3
execute-queryExecutes a SQL query using BigQuery dialectlist-tablesLists all tables in the BigQuery databasedescribe-tableDescribes the schema of a specific tableEnvironment Variables
--projectrequiredThe GCP project ID--locationrequiredThe GCP location (e.g. europe-west9)--datasetSpecific BigQuery datasets to consider--key-filePath to a service account key fileTry it
Original README from codearranger/mcp-server-bigquery
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
Configuration
The server can be configured with the following arguments:
--project(required): The GCP project ID.--location(required): The GCP location (e.g.europe-west9).--dataset(optional): Only take specific BigQuery datasets into consideration. Several datasets can be specified by repeating the argument (e.g.--dataset my_dataset_1 --dataset my_dataset_2). If not provided, all datasets in the project will be considered.--key-file(optional): 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 claude
Claude 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:
- Sync dependencies and update lockfile:
uv sync
- Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
uv publish
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token:
--tokenorUV_PUBLISH_TOKEN - Or 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-bigquery
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.