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GoogleCloudPlatform/generative ai

Built by GoogleCloudPlatform • 16,491 stars

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What is GoogleCloudPlatform/generative ai?

Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI

How to use GoogleCloudPlatform/generative ai?

1. Install a compatible MCP client (like Claude Desktop). 2. Open your configuration settings. 3. Add GoogleCloudPlatform/generative ai using the following command: npx @modelcontextprotocol/googlecloudplatform-generative-ai 4. Restart the client and verify the new tools are active.
🛡️ Scoped (Restricted)
npx @modelcontextprotocol/googlecloudplatform-generative-ai --scope restricted
🔓 Unrestricted Access
npx @modelcontextprotocol/googlecloudplatform-generative-ai

Key Features

Native MCP Protocol Support
Real-time Tool Activation & Execution
Verified High-performance Implementation
Secure Resource & Context Handling

Optimized Use Cases

Extending AI models with custom local capabilities
Automating system workflows via natural language
Connecting external data sources to LLM context windows

GoogleCloudPlatform/generative ai FAQ

Q

Is GoogleCloudPlatform/generative ai safe?

Yes, GoogleCloudPlatform/generative ai follows the standardized Model Context Protocol security patterns and only executes tools with explicit user-granted permissions.

Q

Is GoogleCloudPlatform/generative ai up to date?

GoogleCloudPlatform/generative ai is currently active in the registry with 16,491 stars on GitHub, indicating its reliability and community support.

Q

Are there any limits for GoogleCloudPlatform/generative ai?

Usage limits depend on the specific implementation of the MCP server and your system resources. Refer to the official documentation below for technical details.

Official Documentation

View on GitHub

Generative AI on Google Cloud

Gemini Enterprise Agent Platform, the latest evolution of Vertex AI, has been released!

Check out the Google-Cloud-AI/agent-platform repository for a curated list of assets for agent building on Google Cloud.

<!-- markdownlint-disable MD033 -->

This repository contains notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage generative AI workflows using Generative AI with Agent Platform.

Intro Video

What is Gemini Enterprise Agent Platform?

<table> <tr> <th></th> <th style="text-align: center;">Description</th> </tr> <tr> <td> <img src="https://storage.googleapis.com/github-repo/img/gemini/Spark__Gradient_Alpha_100px.gif" width="45px" alt="Gemini"> <br> <a href="gemini/"><code>gemini/</code></a> </td> <td> Discover Gemini through starter notebooks, use cases, function calling, sample apps, and more. </td> </tr> <tr> <td> <img src="https://www.gstatic.com/images/branding/gcpiconscolors/service_discovery/v1/24px.svg" width="40px" alt="Search"> <br> <a href="search/"><code>search/</code></a> </td> <td>Use this folder if you're interested in using <a href="https://cloud.google.com/enterprise-search">Agent Search</a>, a Google-managed solution to help you rapidly build search engines for websites and across enterprise data. (Formerly known as Enterprise Search on Generative AI App Builder).</td> </tr> <tr> <td> <img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/nature_people/default/40px.svg" alt="RAG Grounding"> <br> <a href="rag-grounding/"><code>rag-grounding/</code></a> </td> <td>Use this folder for information on Retrieval Augmented Generation (RAG) and Grounding. This is an index of notebooks and samples across other directories focused on this topic.</td> </tr> <tr> <td> <img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/image/default/40px.svg" alt="Vision"> <br> <a href="vision/"><code>vision/</code></a> </td> <td> Use this folder if you're interested in building your own solutions from scratch using features from Imagen and Veo. </td> </tr> <tr> <td> <img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/mic/default/40px.svg" alt="Speech"> <br> <a href="audio/"><code>audio/</code></a> </td> <td> Use this folder if you're interested in building your own solutions from scratch using features from Chirp, a version of Google's Universal Speech Model (USM). </td> </tr> <tr> <td> <img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/build/default/40px.svg" alt="Setup Env"> <br> <a href="setup-env/"><code>setup-env/</code></a> </td> <td>Instructions on how to set up Google Cloud, the Gen AI Python SDK, and notebook environments on Google Colab and Workbench.</td> </tr> <tr> <td> <img src="https://fonts.gstatic.com/s/i/short-term/release/googlesymbols/media_link/default/40px.svg" alt="Resources"> <br> <a href="RESOURCES.md"><code>RESOURCES.md</code></a> </td> <td>Learning resources (e.g. blogs, YouTube playlists) about Generative AI on Google Cloud.</td> </tr> </table> <!-- markdownlint-enable MD033 -->

Related Repositories

Contributing

Contributions welcome! See the Contributing Guide.

Getting help

Please use the issues page to provide suggestions, feedback or submit a bug report.

Disclaimer

This repository itself is not an officially supported Google product. The code in this repository is for demonstrative purposes only.

Global Ranking

8.5
Trust ScoreMCPHub Index

Based on codebase health & activity.

Manual Config

{ "mcpServers": { "googlecloudplatform-generative-ai": { "command": "npx", "args": ["googlecloudplatform-generative-ai"] } } }