Provides BigQuery financial operations (FinOps) capabilities for analyzing and monitoring BigQuery costs and usage data within Google Cloud projects
Google Cloud Service Account (Recommended for Production)
Steps:
bash# Create service account
gcloud iam service-accounts create bigquery-finops
--display-name="BigQuery FinOps MCP Server"
Grant permissions
gcloud projects add-iam-policy-binding YOUR_PROJECT_ID
--member="serviceAccount:bigquery-finops@YOUR_PROJECT_ID.iam.gserviceaccount.com"
--role="roles/bigquery.admin"
Create and download key
gcloud iam service-accounts keys create service-account-key.json
--iam-account=bigquery-finops@YOUR_PROJECT_ID.iam.gserviceaccount.com
Move key to your project folder
move service-account-key.json C:\Users\User\bigquery_MCP\
#########################################################
Navigate to directory
cd C:\Users\User\bigquery_MCP example
Install dependencies
python -m pip install --upgrade pip python -m pip install mcp google-cloud-bigquery google-auth pandas numpy python-dotenv
Authenticate with Google Cloud
gcloud auth application-default login gcloud config set project YOUR_PROJECT_ID
Run test
python test_mcp.py
If all tests pass, restart Claude Desktop
Summary: Your Next Steps
Create the folder structure in C:\Users\User\bigquery_MCP
Save the MCP server code as bigquery_finops_mcp.py
Create requirements.txt and run pip install
Set up Google Cloud auth (choose gcloud or service account)
Create config.json with your project settings
Update Claude Desktop config with the correct path
Run the test script to verify everything works
Restart Claude Desktop
Test it out by asking me to show your BigQuery costs!
This server cannot be installed
local-only server
The server can only run on the client's local machine because it depends on local resources.
Enables cost optimization and financial operations for Google BigQuery through natural language interactions. Provides insights into BigQuery spending, usage patterns, and cost management recommendations.