rohithay/dataops-mcp-server
If you are the rightful owner of dataops-mcp-server and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
The GCP Cost Optimization Multi-Agent MCP Server is designed to help organizations manage and optimize their Google Cloud Platform (GCP) expenditures through advanced AI and machine learning techniques.
Tools
Functions exposed to the LLM to take actions
get_bigquery_costs
Retrieve BigQuery cost breakdowns by date, project, user, dataset, etc.
analyze_query_cost
Predict query cost before execution and get AI-based optimization suggestions.
detect_cost_anomalies
Detect unusual spending using ML and get early budget overrun alerts.
optimize_query
Use LLMs to auto-optimize SQL queries with explanations and savings estimates.
create_optimization_pr
Auto-generate GitHub PRs with cost-saving SQL and tests.
send_cost_alert
Send cost alerts to Slack with context and recommended actions.
get_dbt_model_costs
Analyze dbt model costs and suggest materialization improvements.
monitor_sla_compliance
Track SLA compliance and cost-performance trade-offs.
forecast_costs
Forecast future costs and recommend budget plans.
slack_post_message
Post a new message to a Slack channel.
Prompts
Interactive templates invoked by user choice
No prompts
Resources
Contextual data attached and managed by the client