# Contributing
## Local Installation
1. Install the server locally:
```
claude mcp add bigquery --scope user --transport stdio -- uv --directory {{PATH_TO_REPO}} run mcp-server-bigquery --project {PROJECT_ID} --location {{LOCATION}}
```
2. Start Claude Code: `claude`
3. After every change, reconnect the MCP server: `/mcp`, `bigquery`, `Reconnect`
## Building and Publishing
To prepare the package for distribution:
1. Increase the version number in `pyproject.toml`
2. Sync dependencies and update lockfile:
```bash
uv sync
```
3. Build package distributions:
```bash
uv build
```
This will create source and wheel distributions in the `dist/` directory.
4. 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.
