Build a Multi-Agent System From Scratch¶
The companion library for Build a Multi-Agent System — With MCP and A2A (Manning). Learn how LLM agents work by building one yourself, from first principles, step by step.
Available now through Manning's Early Access Program (MEAP) — buy today and get each chapter as it's completed.
About the Book¶
Multi-agent systems and the LLM agents that power them are among the most discussed topics in AI today. There are already many capable frameworks out there — the goal of this book isn't to replace them, but to help you deeply understand how they work by having you build one yourself, from scratch.
All the code lives in the book's own hand-rolled agent framework, primarily designed for educational purposes rather than production deployment. It will give you the foundation to work more confidently with any other LLM agent framework of your choosing, or even to build your own specialised solutions.
The book's learning arc: build the foundations in Part 1, extend your agent in Part 2, and connect agents into a full MAS in Part 3.
Build Your First LLM Agent¶
Start from scratch. Understand what LLM agents and MAS really are, build
tools with SimpleFunction and PydanticFunction, integrate a local Ollama
LLM, and assemble the full LLMAgent class.
Enhance Your LLM Agent¶
Extend your agent with MCP Tools, composable Skills, short- and long-term Memory, and Human-in-the-Loop patterns, with each chapter adding a new capability on top of what you already built.
Build Multi-Agent Systems¶
Connect multiple LLM agents into a collaborative MAS using the Agent2Agent (A2A) protocol, distributing work across agents that communicate, coordinate, and act together.
The LLMAgent you build through the book: a backbone LLM, a set of tools, and a single .run() method to kick it all off.
From the Book¶
Each chapter builds on the last, progressively deepening your understanding from core concepts to full multi-agent systems:
Part 1 — Build Your First LLM Agent¶
| Ch | Title | Notebook |
|---|---|---|
| 1 | What Are LLM Agents and Multi-Agent Systems? | — |
| 2 | Working with Tools | Ch 2 |
| 3 | Working with LLMs | Ch 3 |
| 4 | The LLM Agent Class | Ch 4 |
Part 2 — Enhance Your LLM Agent¶
| Ch | Title | Notebook |
|---|---|---|
| 5 | MCP Tools | Ch 5 |
| 6 | Skills | — |
| 7 | Memory | — |
| 8 | Human in the Loop | — |
Part 3 — Building Multi-Agent Systems¶
| Ch | Title | Notebook |
|---|---|---|
| 9 | Multi-Agent Systems with Agent2Agent | — |
More Examples¶
A selection of additional worked examples showing the framework applied to real integrations. Each explores a different use case you can adapt for your own projects.
GitHub MCP¶
Walk through connecting the agent to the official GitHub MCP server. Discover its available tools and run a simple query — a hands-on look at real-world MCP integration.
GoodNews MCP¶
Connect to the GoodNews MCP server to get good news delivered straight to your LLM agent.
Capstone Projects¶
Capstones are larger, end-to-end projects that pull together what you have built in the book and apply it to something closer to a real-world system.
Monte Carlo Estimation of Pi¶
Orchestrate parallel tool calls to estimate π using the Monte Carlo method.
A great first capstone that exercises the full LLMAgent class.
Deep Research Agent¶
Coming soon. An autonomous research agent that plans searches, synthesises results, and produces structured reports on any topic you give it.
OpenClaw Personal Assistant¶
Coming soon. Build a personal assistant with persistent memory, skill composition, and human-in-the-loop checkpoints using your own framework.
Community¶
The framework is open source and built to be extended. Have you built a new tool integration, a custom agent, or an interesting notebook? Share it with other readers. A dedicated community showcase page is in the works.