google-cloud-mcp

# Google Cloud MCP Server A comprehensive Model Context Protocol (MCP) server for Google Cloud Platform services. This project provides Python wrapper modules and MCP tools for managing various GCP services including BigQuery, Cloud Logging, Cloud Storage, and Compute Engine. ## 🚀 Features - **BigQuery**: Data warehouse operations including query execution, data loading/exporting, job management, and cost estimation - **Cloud Logging**: Comprehensive log management with reading/writing logs, bucket management, sinks, exclusions, and metrics - **Cloud Storage**: Complete bucket and object management with lifecycle policies and batch operations - **Compute Engine**: Virtual machine lifecycle management and zone operations - **MCP Integration**: Full MCP server implementation for AI model interactions - **Flexible Authentication**: Support for both service account files and default credentials ## 📦 Installation ### From PyPI ```bash pip install google-cloud-mcp ``` ### From Source ```bash git clone https://github.com/lockon-n/google-cloud-mcp.git cd google-cloud-mcp pip install -e . ``` ## 🔧 Setup ### Authentication #### Option 1: Service Account (Recommended) 1. Create a service account in Google Cloud Console 2. Download the JSON key file 3. Place it as `service-account-key.json` in your project root #### Option 2: Default Credentials ```bash gcloud auth application-default login ``` ### Running the MCP Server ```bash python main.py ``` ## 🛠️ Available Tools ### BigQuery Tools #### `google-cloud-bigquery_execute_query` Execute SQL queries with optional cost estimation. ```json { "query": "SELECT * FROM dataset.table LIMIT 10", "dry_run": false, "max_results": 1000 } ``` #### `google-cloud-bigquery_create_dataset` Create a new BigQuery dataset. ```json { "dataset_id": "my_dataset", "description": "My dataset description", "location": "US" } ``` #### `google-cloud-bigquery_create_table` Create a new table with schema. ```json { "datas…