When you’re prototyping locally with AI agents like Gemini CLI, Claude Code, or your own agent, their potential is often bottlenecked by your local...
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sweet
What a brilliant use of the Colab MCP Server! Bridging the gap between an AI agent and a live notebook environment is a total game-changer for secure, cloud-based prototyping. Your architecture for handling notebook execution while keeping the local environment clean is impressive
I've just tried it and it's amazing :)
@jmew I hope you don't mind I post this here:
I Stress-Tested Google's Colab MCP Server with a Real Quantum Workflow
Nikoloz Turazashvili (@axrisi) ・ Mar 18
Oh amazing!
Thanks, man! :)
This looks really interesting.
Using Colab as an MCP host makes a lot of sense, especially for agents that need isolated execution.
Does the server support multiple concurrent agent sessions, or is each notebook limited to a single MCP connection?
sandboxing AI agent execution is actually the right move. been running into this with local agents - they can technically run anything and that gets uncomfortable fast. the Colab angle is interesting because you get GPU access for free plus natural isolation. curious whether the MCP protocol adds latency you notice in practice for agentic loops?
the Colab MCP server is useful but the free tier session timeout is the first real problem you hit when an agent is mid task, curious whether Google is offering any way to keep sessions alive longer for MCP connected agents or if you're still subject to the standard 90 minute idle limit
Programmatic cell management is the real unlock here — most MCP integrations stop at code execution. Does the server handle long-running cells that outlive the agent session?
This is a game changer for agent workflows. The notebook-as-artifact approach is smart: instead of getting code dumped in your terminal, you get something you can actually inspect, share, and pick up where the agent left off.
Curious about latency though. When an agent is iterating fast (write cell → execute → read output → write next cell), how does the round-trip feel compared to running locally? And is there a way to pre-warm a Colab runtime so the first cell doesn't eat 10+ seconds on kernel startup?
Cool😉
Nice!