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@@ -12,8 +12,20 @@ A Model Context Protocol server that provides access to BigQuery. This server en
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- 🎯 Dataset filtering for security and performance
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- 🚀 Dual transport support (stdio for local, HTTP/SSE for cloud deployment)
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## Deployment Options
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This server can be deployed in multiple ways to suit different use cases:
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-**📦 PyPI Package** - Install via `uvx` or `uv` for local use with Claude Desktop or other MCP clients
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-**🐳 Docker Hub** - Pre-built multi-architecture images available at [`timoschd/mcp-server-bigquery`](https://hub.docker.com/r/timoschd/mcp-server-bigquery)
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-**☁️ Google Cloud Run** - Deploy as a serverless HTTP/SSE endpoint with automatic scaling
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-**🔧 Local Development** - Use Podman Compose for containerized local development
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All deployment methods support both **stdio** (for local MCP clients) and **HTTP/SSE** (for cloud/remote access) transports.
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## Table of Contents
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-[Deployment Options](#deployment-options)
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-[Components](#components)
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-[Configuration](#configuration)
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-[Quickstart](#quickstart)
@@ -119,7 +131,20 @@ On Windows: `%APPDATA%/Claude/claude_desktop_config.json`
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}
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```
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Replace `{{PATH_TO_REPO}}`, `{{GCP_PROJECT_ID}}`, and `{{GCP_LOCATION}}` with the appropriate values.
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##### Remote Server Configuration (SSE)
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To connect to a remotely deployed server (e.g., on Cloud Run):
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```json
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"mcpServers": {
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"bigquery": {
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"transport": "sse",
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"url": "https://your-server-url.run.app/messages"
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}
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}
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```
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Replace `{{PATH_TO_REPO}}`, `{{GCP_PROJECT_ID}}`, `{{GCP_LOCATION}}`, and `https://your-server-url.run.app` with the appropriate values.
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### Docker Deployment
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timoschd/mcp-server-bigquery:latest
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```
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#### Using Podman Compose
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#### Using Podman Compose/ Docker Compose
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A `podman-compose.yml` file is provided for easy local development:
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# Start the service
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podman-compose up
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```
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OR
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```bash
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docker-compose up
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```
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The compose file supports configurable environment variables:
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