Product guide

Building AI Agents for Network Operations: Python, Ollama, MCP, and Tool Calling

Building AI Agents for Network Operations is a practical guide to creating LLM-supported NetOps workflows with Python, Ollama, MCP, and tool calling. It moves from local-model setup and structured CLI parsing to context-aware troubleshooting agents, approved tools, and read-only pilot planning. The book is aimed at network and operations professionals, with basic networking and CLI familiarity and beginner Python knowledge described as useful.

At a glance

Build local NetOps LLM workflows using Python and Ollama.
Practice turning CLI and BGP output into structured data for validation.
Develop troubleshooting agents that retain context and call approved network tools.
Explore packaging reusable tools with MCP and planning read-only pilots with operational controls.

Price

$28.00Save 38%

Reference price: ~~$44.99~~

Price checked: Nov 14, 2026

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Pros and cons

Pros

Connects agent concepts to concrete NetOps tasks such as interface, reachability, topology, and BGP checks.
The described approach emphasizes validated evidence, approved tool calls, logging, and human review rather than unrestricted network changes.
Covers a progression from local-model labs and mock data through evaluation and production-readiness considerations.

Technical specifications

9 specifications

Book details
Publisher	Packt Publishing
Publication date	July 29, 2026
Edition	1st
Language	English
Print length	226 pages
ISBN-10	1808346831
ISBN-13	978-1808346835

Dimensions and installation
Weight listed	13.9 ounces
Dimensions	7.5 x 0.51 x 9.25 inches

What to know before buying

Listing details to confirm

The listing describes lab agents starting with local models and mock data, while adapting workflows to real network operations is presented as a later step requiring appropriate controls. Basic networking and CLI familiarity are expected, and beginner Python knowledge is useful.

Who is it for?

A good fit for

Network, NetOps, and NOC engineers exploring AI-assisted troubleshooting.
SREs, DevOps engineers, and network-automation professionals who want to build controlled LLM workflows.
Readers with networking and CLI familiarity who can follow basic Python examples.

Less suited to

Readers seeking a general introduction to networking or Python from the ground up.
Buyers looking for a guide centered on autonomous write access to production devices. The described early workflows are read-only.

Customer reviews on Amazon

4.5 / 5 · 21 ratings

5 stars88%88%
4 stars0%0%
3 stars0%0%
2 stars0%0%
1 star12%12%

Aggregate customer ratings lean strongly toward the five-star category, but a smaller one-star portion makes the picture less uniform. This gives a positive but not definitive signal about reader reception. The supplied information does not include written feedback, so it cannot show what readers specifically liked or criticized about the book's NetOps examples or technical depth.

Frequently asked questions

What topics does the book cover?

The listing describes local LLM setup with Ollama and Python, prompt design, parsing CLI and BGP output, chatbot memory, approved tool calling, agentic troubleshooting, MCP, and production-readiness planning.

Does it focus on changing production network devices?

No. The described early agents use local models and mock data, and the book emphasizes read-only pilots, validation, approvals, and human operational decisions.

What background is useful?

The listing says basic networking and CLI familiarity will help, while beginner Python knowledge is useful for following the labs.

What are the book's listed format details?

The listing gives an English-language first edition with 226 pages, published by Packt Publishing.