Model Context Protocol

MCP, an open protocol for connecting models/agents to external tools and data sources through standardized servers. · Official docs

Used in 10 notebooks

Claude with ADK on Vertex AI Agent Engine — Builds and deploys a Claude-powered ADK Reddit agent on Vertex AI Agent Engine with memory and tracing.
Get started with Cloud API Registry on Vertex AI Agent Engine — Builds and deploys an ADK BigQuery data analyst agent using Cloud API Registry on Vertex AI Agent Engine.
MCP on Vertex AI Agent Engine with custom installation scripts — Deploys a Reddit MCP tool agent to Vertex AI Agent Engine with custom install scripts.
Building multi-agent systems with Vertex AI and Claude — Builds a Vertex AI Agent Engine multi-agent market analysis system with Gemini, Claude, ADK, A2A, and MCP.
Building Multi-Agent Systems with Vertex AI and Llama model — Builds a traced Vertex AI multi-agent trading analyst with Gemini, Llama, ADK, A2A, and MCP tools.
Intro to Managed Agents API on Agent Platform (Python) — Shows how to create, inspect, interact with, and delete Managed Agents with google-genai.

Deploying an Agent with Agent Engine and MCP Toolbox for Databases — Deploys a Gemini hotel-booking agent on Agent Engine using Cloud SQL, Cloud Run Toolbox, and LangGraph.
Introduction to Gemini Deep Research Agent — Shows how to run Gemini Deep Research Agent with streaming, multimodal input/output, and grounding tools.
Intro to Model Context Protocol (MCP) integration with Vertex AI — Shows how to connect Gemini on Vertex AI to custom and prebuilt MCP servers.

MCP Server with Gemini Enterprise — Builds an MCP HR leave tool on Cloud Run, connects it to an ADK Gemini agent, and registers it with Gemini Enterprise.