The first walkthrough demonstrates building a Next.js chat app with Gemini CLI, featuring streaming responses, markdown rendering, and model selection.
An initial "bad prompt" was used to show how Gemini CLI handles ambiguous requests and subsequent debugging.
Common issues encountered included updating the screen for streaming tokens, autofocusing input after responses, and displaying markdown.
Gemini CLI successfully implemented autofocus and markdown rendering in one shot when prompted clearly.
The built-in Google search tool was used to find the latest Next.js version when an older version caused problems.
Out-of-date model versions (e.g., Gemini Pro 1.0) were addressed by specifying newer models like Gemini Flash.
Screenshots were used to visually demonstrate issues (e.g., responses getting cut off, appearing in wrong bubbles) to help Gemini CLI debug.
The issue of responses being cut off was resolved by increasing the max output tokens parameter, which was initially low.
Gemini CLI was used to initialize a Git repository, make a first commit, and update a Dockerfile for deployment to Google Cloud Run.
The tool could save a summary of the long conversation to memory for future reference.
Walkthrough 2: Fetching Content with MCPs (DuckDuckGo) 10:43
The built-in web fetch tool requires full URLs and some sites may block Gemini's direct page downloads.
To overcome limitations with Google's search not providing raw URLs, an MCP (Multi-Modal Component) was introduced.
Setting up an MCP involves creating a hidden .gemini directory, a settings.json file inside it, and installing the MCP server (e.g., duck.go MCP server via uv install).
The DuckDuckGo MCP was used to fetch the five most recent articles from TechCrunch, including their titles, URLs, and summaries, successfully retrieving raw URLs.
Walkthrough 3: Hugging Face and Context 7 MCPs for Development 17:45
This walkthrough demonstrated setting up and using Hugging Face and Context 7 MCP servers.
The Hugging Face MCP was used to "giflify" an image from a Dropbox URL, processing it on Gradio Spaces and saving it locally as a WebP image.
The Context 7 MCP, which provides access to documentation, was used to create an Agent Development Kit (ADK) agent.
The ADK agent was designed to answer questions about Gemini CLI and use Google search, configured to run in ADK web (a built-in UI for testing agents).
Initial attempts led to the agent using its own Google search tool, but it was corrected to use Gemini CLI's built-in Google search tool by leveraging Context 7 for ADK documentation.
The final ADK agent successfully ran in the ADK web UI, answered questions about Gemini CLI, and performed accurate Google searches.
The Context 7 MCP is highlighted as a valuable tool for accessing documentation for various development tasks.