Autonomous AI Employees with n8n and MCP: Build Self-Healing Agent Teams That Plan, Use Tools, Remember, Ask for Approval, and Run Reliably Without Constant Supervision (AI Agents & MCP Series) by Leandro Calado
English | August 7, 2026 | ASIN: B0HD9TTFDY | 368 pages | EPUB | 0.78 Mb
Most AI agents do not fail because they cannot reason.
They fail because production is messy.
An API returns a 429 error. A tool times out. Memory becomes contaminated. One agent waits forever while another reports success even though nothing happened. A retry turns into an infinite loop. An irreversible action is executed without approval.
Autonomous AI Employees with n8n and MCP shows you how to engineer those failures out of your agent systems.
This is not another collection of toy chatbots or copy-and-paste demonstrations. It is a practical, production-focused guide to building bounded, observable and self-healing agent teams that can perform real work without requiring constant supervision.
Inside, you will learn how to:
* Define clear agent contracts, permissions, budgets and stopping conditions
* Implement the plan-act-verify operating loop
* Connect agents to n8n, APIs and MCP tools safely
* Persist state, create checkpoints and resume interrupted work
* Build memory that learns without accumulating unreliable information
* Add human approval only where risk requires it
* Coordinate supervisors, specialists and verification agents
* Prevent infinite loops, duplicate actions and runaway costs
* Trace decisions and evaluate agent behavior systematically
* Recover through retries, replanning, fallback and rollback
* Protect credentials, isolate tenants and defend against prompt injection
* Assemble a complete Autonomous Business Operations Team
The book contains 15 chapters, 18 practical appendices and implementation patterns validated by 79 automated tests.
It is written for n8n builders, automation engineers, developers, technical founders and AI architects who are ready to move beyond impressive demonstrations and build agents that can prove their work.
If you want autonomous AI systems that are not merely intelligent-but dependable-this is the operating manual.
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