GCP Official MCP Server

Overview

GCP Official MCP Server consists of Google Cloud Platform's four official remote MCP servers announced in December 2025. These operational servers span dataset operations, virtual machine management, Kubernetes management, and comprehensive GCP service integration, enabling AI-driven cloud automation on Google Cloud.

Official MCP Servers

1. BigQuery Dataset Operations

• Query datasets with natural language
• Run SQL queries
• Manage datasets and tables
• Export and import data
• Access public datasets
• Data analytics and insights

2. Compute Engine VM Management

• Create and manage VM instances
• Start, stop, and delete VMs
• Configure machine types
• Manage disks and snapshots
• Network configuration
• SSH key management

3. Google Kubernetes Engine (GKE)

• Create and manage GKE clusters
• Deploy applications
• Scale workloads
• Manage node pools
• Configure networking
• Access cluster resources

4. Comprehensive GCP Services

• Cloud Storage operations
• Cloud Functions deployment
• Cloud Run services
• Cloud SQL databases
• IAM management
• Resource monitoring

Features

• Remote MCP Servers: Hosted by Google Cloud, no local installation
• Natural Language Interface: Interact with GCP using conversational AI
• Full API Integration: Access to complete GCP service catalog
• Authentication: OAuth2 with Google Cloud authentication
• Project Management: Multi-project support
• Resource Discovery: Automatic resource enumeration
• Cost Monitoring: Track resource usage and costs
• Security Controls: IAM and access management

BigQuery Capabilities

• Ad-hoc SQL queries
• Data warehouse operations
• Analytics and reporting
• Machine learning integration
• Public dataset access
• Data export and sharing
• Table schema management

Compute Engine Features

• Custom machine types
• Preemptible VMs
• Instance templates
• Managed instance groups
• Load balancing
• Auto-scaling
• Metadata management

GKE Operations

• Cluster creation and deletion
• Workload deployment (kubectl-like operations)
• Service exposure
• Ingress configuration
• Resource quotas
• Logging and monitoring
• Helm chart deployment

Use Cases

• Automate GCP infrastructure management
• Run BigQuery analytics through AI conversations
• Deploy and manage Kubernetes workloads
• Monitor cloud resource usage and costs
• Implement AI-driven DevOps workflows
• Build GCP automation tools
• Create conversational cloud interfaces

Enterprise Integration

• Organization-level access
• Multi-project management
• Shared VPC support
• Service accounts
• Audit logging
• Compliance controls
• Budget alerts

Authentication

• Google Cloud OAuth2
• Service account credentials
• Workload identity
• API key support
• Fine-grained IAM permissions

Pricing

Free MCP servers from Google Cloud. GCP service usage follows standard pricing:

• Free Tier: $300 credit for new users
• Pay-as-you-go: Resource-based pricing
• Committed Use: Discounts for long-term commitments
• Enterprise: Custom pricing and support