https://github.com/MCP-Mirror/LucasHild_mcp-server-bigquery
Mirror of https://github.com/LucasHild/mcp-server-bigquery
https://github.com/MCP-Mirror/LucasHild_mcp-server-bigquery
Last synced: about 2 months ago
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Mirror of https://github.com/LucasHild/mcp-server-bigquery
- Host: GitHub
- URL: https://github.com/MCP-Mirror/LucasHild_mcp-server-bigquery
- Owner: MCP-Mirror
- License: mit
- Created: 2024-12-25T19:33:03.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-12-25T19:33:07.000Z (10 months ago)
- Last Synced: 2024-12-25T20:27:42.523Z (10 months ago)
- Language: Python
- Size: 0 Bytes
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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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 dialect
- `list-tables`: Lists all tables in the BigQuery database
- `describe-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 tables in the project will be considered.
## Quickstart
### Install
#### 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Development/Unpublished Servers Configuration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:
1. Sync dependencies and update lockfile:
```bash
uv sync
```
2. Build package distributions:
```bash
uv build
```
This will create source and wheel distributions in the `dist/` directory.
3. Publish to PyPI:
```bash
uv publish
```
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token: `--token` or `UV_PUBLISH_TOKEN`
- Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--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](https://github.com/modelcontextprotocol/inspector).
You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:
```bash
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.