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Lately, I’ve been diving deep into Gemini CLI and experimenting with multiple MCP integrations. I started by connecting Context7, which fetches real-time, version-specific docs and code snippets right into your prompt — super useful for quick reference and building faster.

Then I added Taskmaster-AI, which lets me tap into both OpenAI and Google API keys. This unlocked a much broader range of language models for different use cases like planning, summarizing, or automation.

To top it off, I included SmolAgents, a lightweight agent framework from GitHub that allows for modular, goal-driven AI behavior directly in the terminal.

What surprised me is how seamlessly these all work together inside Gemini CLI. You don’t need to call them out directly — once configured properly in your .gemini/settings.json, they complement each other naturally. Taskmaster handles structured planning, Context7 brings up-to-date references, and SmolAgents give flexible control.

I’m curious if anyone else is combining tools like these in their workflow? What kinds of prompts or workflows are you using Gemini CLI for?

Also, if you're interested, I made a quick walkthrough, check out the link in my profile.

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  • 2
    I actually am making my own MCP server to aggregate things like this, plus more like http endpoint
  • 1
    Who downvoted this? Genuine info. Will check the github later.

    I have to find out still how mcp servers actually are connected to your llm. I do function calling and stuff but that's something different? Kinda lost.
  • 0
    @retoor They are pretty much the same thing, it's a way to register a bunch of functions dynamically
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