Coding with Gemini CLI and the Developer Knowledge API
Enabling The Developer API support with MCP to streamline Google Cloud Development ...
Google Cloud
MCP Development with C++, Cloud Run, Firestore, and Gemini CLI
Leveraging Gemini CLI and the underlying Gemini LLM to build Model Context Protocol (MCP) AI...
Welcome to MCP-P-A-looza
An overview of current Model Context Protocol (MCP) implementations across the programming landscape.
MCP Development with Haskell and Gemini CLI
Leveraging Gemini CLI and the underlying Gemini LLM to build Model Context Protocol (MCP) AI...
Building Collaborative AI Agent Ecosystems: A Deep Dive into ADK, MCP & A2A with Pokemon
Introduction: The Future of AI is Collaborative Imagine asking an AI agent about Pokémon...
Introduction: The Future of AI is Collaborative
Imagine asking an AI agent about Pokémon and getting not just basic information, but comprehensive analysis comparing battle statistics, type effectiveness calculations, and fun trivia — all generated through seamless collaboration between specialized AI agents. This isn’t science fiction; it’s what we can build today using Google’s cutting-edge agent technologies.
How to Get Automatic Code Review Using LLM Before Committing
Traditional code reviews can be time-consuming and prone to human error. To streamline this process...
Traditional code reviews can be time-consuming and prone to human error. To streamline this process and enhance code quality, developers are increasingly turning to AI-powered solutions. In this blog post, you'll explore how to leverage Code Llama, a cutting-edge AI model for code analysis, in conjunction with Docker to create an efficient and automated code review workflow. By integrating Code Llama into your local development environment, you can catch potential issues early in the development cycle, reduce the burden on human reviewers, and ultimately deliver higher-quality code. This guide is designed for developers of all levels who want to improve their coding practices.