About mcp-server-bigquery-fastmcp
mcp-server-bigquery-fastmcp is an MCP server published by fastmcp-me in the Data category: a Model Context Protocol server that provides access to BigQuery. This server enables LLMs to inspect database schemas and execute queries.
Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
uvx mcp-server-bigquery-fastmcppip install mcp-server-bigquery-fastmcpThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Tools (3)
describe-tableDescribes the schema of a specific table
Parameters not published.
execute-queryExecutes a SQL query using BigQuery dialect
Parameters not published.
list-tablesLists all tables in the BigQuery database
Parameters not published.
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README
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 either with command line arguments or environment variables.
| Argument | Environment Variable | Required | Description |
|---|---|---|---|
--project |
BIGQUERY_PROJECT |
Yes | The GCP project ID. |
--location |
BIGQUERY_LOCATION |
Yes | The GCP location (e.g. europe-west9). |
--dataset |
BIGQUERY_DATASETS |
No | 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) or by joining them with a comma in the environment variable (e.g. BIGQUERY_DATASETS=my_dataset_1,my_dataset_2). If not provided, all datasets in the project will be considered. |
--key-file |
BIGQUERY_KEY_FILE |
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 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:
-
Increase the version number in
pyproject.toml -
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.
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.