mcpField
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gcp-functions

gcp-functions

github.com/alphaonedevCloud & DevOps46 installs
Repository

About gcp-functions

gcp-functions is a skill for planning and operating Google Cloud resources, aimed at agents using the Google Cloud Python SDK for execution. It covers architecture choices, cost modeling, identity prerequisites, and Vertex AI workflow design.

Key features

  1. 01GCP service and architecture guidance
  2. 02Cost estimation and optimization
  3. 03IAM and identity federation prerequisites
  4. 04IaC approach references
  5. 05Vertex AI agent workflow design

Use cases

  1. 01Compare GCP services and deployment approaches
  2. 02Estimate cloud resource costs
  3. 03Check IAM and Workload Identity Federation prerequisites
  4. 04Plan Vertex AI multi-agent workflows

MCP support

The README notes that Vertex AI Extensions are MCP-compatible; it does not describe this skill as an MCP server or connection manager.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/alphaonedev/openclaw-graph --skill gcp-functions

After installing, type/gcp-functionsin Claude Code to confirm it loaded.

Details

From the project README

gcp-functions

Google Cloud Integration

This skill delegates all GCP provisioning and operations to the official Google Cloud Python client libraries.

# Core GCP client library
pip install google-cloud-python

# Vertex AI + Agent Engine (AI/ML workloads)
pip install google-cloud-aiplatform

# Specific service clients (install only what you need)
pip install google-cloud-bigquery      # BigQuery
pip install google-cloud-storage       # Cloud Storage
pip install google-cloud-pubsub        # Pub/Sub
pip install google-cloud-run           # Cloud Run

SDK Docs: https://github.com/googleapis/google-cloud-python Vertex AI SDK: https://cloud.google.com/vertex-ai/docs/python-sdk/use-vertex-ai-python-sdk

Use the Google Cloud Python SDK for all GCP provisioning and operational actions. This skill provides architecture guidance, cost modeling, and pre-flight requirements — the SDK handles execution.

Architecture Guidance

Consult this skill for:

  • GCP service selection and trade-off analysis
  • Cost estimation and optimization (committed use discounts, sustained use)
  • Pre-flight IAM / Workload Identity Federation requirements
  • IaC approach (Terraform AzureRM vs Deployment Manager vs Config Connector)
  • Integration patterns with Google Workspace and other GCP services
  • Vertex AI Agent Engine for multi-agent workflow design

Agent & AI Capabilities

CapabilityTool
LLM agentsVertex AI Agent Engine
Model servingVertex AI Model Garden
RAGVertex AI Search + Embeddings API
Multi-agentAgent Development Kit (google/adk-python)
MCPVertex AI Extensions (MCP-compatible)

Reference

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