AgentNotebook

Tag

#Tool use

3 posts tagged.

From scratch

Build your first AI agent from scratch in 30 minutes

An AI agent is just a loop: you call a model, the model asks to run a tool, you run it, you feed the result back, and you repeat until the model is done. In this tutorial you build that loop yourself in plain TypeScript against the Anthropic Messages API — no framework. You will wire up two tools (read a file, run a calculation), let the model orchestrate them, add a turn cap and basic guardrails, then verify the whole thing end to end. The result is a small research agent you fully understand and can extend with your own tools.

12 min read4
Add to SaaS

Add an AI agent to an existing SaaS without rewriting it

You do not need to rebuild your product to ship an AI agent inside it. The trick is to expose the service functions you already have — search records, create an order, fetch a customer — as tools, then run a small server-side agent loop that the model uses to orchestrate them. This tutorial wraps an existing service layer as tools, scopes every call to the authenticated user, separates safe read tools from gated write tools, exposes the agent as one authenticated endpoint, and deploys that endpoint to Totalum. Your database, auth, and business logic stay untouched.

13 min read4
MCP servers

Write your first MCP server and wire it to Claude

The Model Context Protocol (MCP) is a standard way to expose tools to any MCP-capable client — Claude Desktop, IDEs, or your own agents — so you write an integration once and reuse it everywhere. In this tutorial you build an MCP server in TypeScript that exposes a single typed tool over the stdio transport, test it with the MCP Inspector, then register it with Claude and call it from a real conversation. You will also learn the one rule that trips up everyone on stdio: never write to stdout. By the end you have a reusable server you can extend with your own tools.

12 min read4