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Build a Nanobot-Style AI Agent in Google Colab with Tool Calling, Session Memory, Skills, and MCP Servers

A tutorial demonstrates building a lightweight AI agent in Google Colab inspired by nanobot architecture, covering tool calling, session memory, skills, and MCP servers. The agent is built from scratch to illustrate how messages, tools, memory, and model responses integrate. The result is a provider-agnostic agent loop extendable to real LLM providers and production tools.

read1 min views1 publishedJun 26, 2026

In this tutorial, we build a lightweight personal AI agent inspired by the architecture of nanobot, runnable entirely in Google Colab. We start from a provider abstraction, then add tool registration, session memory, lifecycle hooks, skills, and an MCP-style tool server. Rather than rely on an external framework, we recreate each building block ourselves to see how messages, tools, memory, and model responses fit together. The result is a provider-agnostic agent loop we can extend toward real LLM providers and production tools.

The post Build a Nanobot-Style AI Agent in Google Colab with Tool Calling, Session Memory, Skills, and MCP Servers appeared first on MarkTechPost.

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