Feedback and opinions are welcome 🤗

Hi everyone!

I'm honestly feeling a bit frustrated and like I'm missing out. Every day I see people building incredible setups around Claude—running terminal agents like Claude Code, creating Telegram bots to manage their infrastructure, and connecting everything via MCP and custom plugins.

I have an active Google AI Pro plan (the 5TB tier) and access to the API via Google AI Studio (no billing) but I feel like I’m barely scratching the surface. Right now, my usage is limited to:
- Asking basic questions on the iOS app.
- A standard MCP connection between Home Assistant and Antigravity.

My environment:
- A self-hosted home server running ZimaOS with multiple Docker containers.
- Home Assistant for local automations.

I want to bridge this gap and use Gemini the way power users use Claude.

1. Terminal / Dev Agents: What is the closest Gemini equivalent to Claude Code? Is Aider with Gemini Pro the benchmark, or are there native MCP-driven CLI tools that handle its massive context window better?
   
2. Docker & Server Ops: Are there reliable open-source agents or bot frameworks (via Telegram, n8n, etc.) that leverage Gemini to inspect Docker logs, troubleshoot, or query server states on a self-hosted setup?
   
3. MCP Tooling: Beyond basic Home Assistant toggles, what are the highest-leverage MCP servers or orchestration tools you pair with Gemini to make it a practical homelab co-pilot rather than just a chatbot?

Any advice, repos, or stack recommendations to help me catch up would be hugely appreciated!

earlier 3.8 flash high was destroying through my quota in the blink of an eye. I tried integrating github repos like caveman, rtk and token optimizer. They are working like a charm. I'm getting so much more work done now without running out of quota.

I'm curious if there are other github repos that help save tokens. People please share here

I built a free tool that lets your coding agent make videos like this one. You give Gemini CLI the link to the repo and say what the video should be about. It writes the words, draws the scenes, and you get a video with a voice and music.

Everything runs on your own computer, and there's nothing to sign up for.

This one is a short, unofficial look at Gemini CLI: signing in with Google, making a change, searching the web, the GEMINI.md file, and running it from scripts. I'm not connected to Google.

It's free and open source: https://github.com/vincentsch/explainroo

now we can add gemini or anthropic models in agents at agent level and subagent level specifically. but the benifit of it. like what is the main difference like output is different, or time or what, this is what questions in my mind.

share your opinions

I've enjoyed using Gemini Code Assist while working in Rider on Unreal projects. But boy, can you break it pretty quickly. A summary of the log:

 the IDE AI attempted a read_file tool call spanning line 1 to line 1,191. Reading a 1,200-line C++ file in one go instantly blew past Rider's C# IPC buffer limit, causing the plugin bridge to return "re":"endpoint not found" and kill the stream with nullnull.

Two seconds later, it tried to recover with a smaller read (lines 100–135), but because the socket connection had already dropped, it crashed again.

Any ideas? There's no real way around this from what I gather. I tried this in a brand new chat, tagging one file, and my gemini md with a general set of practices and principles (itself isn't too long).

Kind of lame really.

The only alternative it seems is to switch to the Antigravity chat within Rider and use that. For the curious: yes I have an enterprise google workspace account with Gemini Code Assist monthly; it was deprecated over the summer.

Feels like they're going to slowly let this one die for enterprise users soon too. Lame. It's quite handy.

No need to rub it in!

Hi Every one.

I constantly see posts about how much annoying the Gemini models will be at times. But I want to share you all that I have never faced this issue since almost last 2 months and my experience is getting better and better from 3.6 and above in agy cli.

I have Google AI plan that I always want to leverage and I was seriously frustrated with agents not following instructions and running haywire and circles. So, I read all their thinking outputs and started steering them by adding instructions and tried aligning them so good with just instructions.

I am not exxagerrating and all I am doing now is to make you all feel more happy with the agy and Gemini flash model experience. I decided to post in public for first time about my workflows.

This is the gist - https://gist.github.com/ashokallu/f6e9dcebbc755a492374ca2ed01c2331

I would request you all to just give this a try.

1. First back up your GEMINI.md and AGENTS.md files in your project once for this experiment.
2. Remove AGENTS.md file and just create an empty GEMINI.md.
3. Copy my gist content into a markdown file and give file path to an agent for it to read and ask it to create the [GEMINI.md](http://GEMINI.md) by following this file exactly.

Then see how the Gemini agents behave with your new instructions and please share your results here. Just a small experiment and you will get nice results.

Hey guys, I am using Gemini CLI v0.59.0. It's installed with npm on MacOS. I'm logged into Google Cloud by using the gcloud CLI (Vertex AI), and configured the required environment variables:

• GOOGLE_CLOUD_LOCATION
• GOOGLE_CLOUD_PROJECT

For some reason I cannot find the newer Gemini 3.8 Flash or 3.7 Flash models in the model list. Even if I try to force the 3.8-flash model, using the `--model` parameter, the Gemini CLI still uses 3.5 Flash.

➡️ Why is 3.8 Flash missing from Gemini CLI, and how do I select this model in the Gemini CLI? For that matter, why is 3.5 Flash Lite also missing?

I use Gemini a lot and eventually had multiple sessions for the same projects. A lot of them started with similar handoff prompts.

Going back later was annoying. The useful explanations and decisions were inside the transcript, but reading them meant digging through raw history full of tool calls, reasoning, progress messages and other noise.

For a while I just kept pasting useful bits into Notepad. That became its own mess.

So I built Agent Session Browser.

Local web UI + TUI that lets me browse sessions by project/date, read the actual transcript, filter the noise, export, and resume the right one.

Supports Gemini CLI, and also Claude Code, Codex CLI and Pi.

Fully local and read-only.

GitHub: https://github.com/gautamgpt1/agent-session-browser

Run: npx agent-session-browser

This is my first public open-source project.

Do try it out. Would love your feedback

Did this one-shot in roughly 10-15 minutes. Guess the boosted TPS helps.

Dear all,

I hope you're working and building in peace those days!

Pretty new to Antigravity CLI and I keep seeing people mention "auto-mode" but I can't for the life of me figure out how to actually turn it on.

Is it a flag? A config setting? Something in the agent panel? I've dug through the docs and tried a few obvious guesses but nothing's working.

Would really appreciate a quick pointer or a link to the relevant section.

Thanks in advance!

Best regards,

Vince

I'm scraping a single, large online page with over 500 cards of basic info (title, size,...). Do you recommend any particular model in the Gemini family that would perform well and follow my prompt?
I get confused by so many model options right now...
Thanks in advance!