Developer Knowledge Concierge

Build Faster on Google Cloud

Instant, grounded architectural guidance, SDK code snippets, and official GCP documentation powered by conversational AI.

Launch Query Sandbox

$ gcloud components update

concierge-sandbox // interactive-prompt-launcher

MCP Protocol v1.0 • Ready for Query

Select Category Quick-Start

Compute & Serverless Click to copy

"How do I deploy a container to Cloud Run with automatic scaling, concurrency tuning, and custom domain mapping?"

CLI: gcloud run deploy Execute ↗

Storage & Databases Click to copy

"What are the best practices for BigQuery table partitioning and clustering to optimize slot utilization and scan costs?"

SQL: PARTITION BY date Execute ↗

IAM & Security Click to copy

"How do I configure Google Secret Manager with Workload Identity Federation for keyless authentication on GKE/Cloud Run?"

IAM: secretmanager.secretAccessor Execute ↗

AI & ML Click to copy

"How can I integrate Gemini 1.5 Pro via Vertex AI Python SDK with streaming responses and function calling tools?"

SDK: google-cloud-aiplatform Execute ↗

query$

Foundation & Architecture

Curated Documentation Pillars

Core building blocks optimized for resilient production workloads across compute, data, and defense-in-depth security.

gcloud run deploy

Cloud Run & Serverless

Deploy containerized services effortlessly with automated scale-to-zero and granular traffic splitting. Minimize operational overhead while maintaining microsecond responsiveness.

Compute • VPC Access Read Guide

bq query --use_legacy_sql=false

BigQuery & Analytics

Execute petabyte-scale data warehouse queries with built-in ML integrations and partition pruning. Streamline batch and real-time analytical workflows with zero provisioning.

Analytics • BigLake Read Guide

gcloud secrets create

Security & Secret Manager

Enforce least privilege with Workload Identity and automated Secret Manager replication. Safeguard sensitive API credentials and database keys with auditable IAM bindings.

Security • IAM Policies Read Guide

Production Lifecycle

Quickstart Architecture & Workflow

An engineering-first progression from initial project scaffolding to enterprise MCP agent query routing.

01. Scaffold Project Workspace

Environment Setup

Initialize your local repository, configure Git remotes, and set your default Google Cloud target project and compute region.

# Configure gcloud CLI context

gcloud config set project PROJECT_ID && gcloud config set run/region europe-west1

02. Configure Secret Manager & IAM

Security Hardening

Provision the Developer Knowledge API key into Secret Manager and grant least-privilege accessor roles to the Gemini Enterprise service agent.

# Provision secret and IAM accessor binding

gcloud secrets add-iam-policy-binding ai-day-oslo \
  --member="serviceAccount:service-${PROJECT_NUMBER}@gcp-sa-ces.iam.gserviceaccount.com" \
  --role="roles/secretmanager.secretAccessor"

03. Deploy with Cloud Run

Container Deployment

Package your service into a secure, distroless container and deploy directly to Cloud Run with public egress and automatic HTTPS.

# Deploy container service

gcloud run deploy gcp-developer-hub \
  --image="gcr.io/${PROJECT_ID}/developer-hub:latest" \
  --allow-unauthenticated \
  --port=8080

04. Query via Developer Knowledge MCP

Conversational Retrieval

Communicate with the Developer Concierge backed by the official Google Developer Knowledge Model Context Protocol (MCP) server.

# GECX MCP Target Endpoint

POST https://developerknowledge.googleapis.com/mcp
Header: X-Goog-Api-Key: <SECRET_RESOLVED_VALUE>