Semantic Kernel, MCP & n8n: A Beginner's Guide to Intelligent Workflows, Tool Calling, and Automation
Language: English
Published by Independently published, 2025
- Softcover
- New
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- Title
- Semantic Kernel, MCP & n8n: A Beginner's Guide to Intelligent Workflows, Tool Calling, and Automation
- Author
- Vexel, Alira
- Publisher
- Independently published
- Publication year
- 2025
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798297521889
Build Production-Ready Smart AI Agents — From Zero to Deployment in Weeks
In 2025, building truly intelligent AI systems means more than just calling an API.
You need context-aware agents that can reason, call tools, remember past interactions, and integrate seamlessly into workflows.
That’s exactly what this book teaches — step-by-step, from beginner to production-grade AI engineer.
In Semantic Kernel, MCP & n8n: A Beginner’s Guide to Intelligent Workflows, Tool Calling, and Automation, you’ll master how to combine Microsoft’s Semantic Kernel, the Model Context Protocol (MCP), and the n8n automation platform to create smart, modular, and extensible AI agents.
These agents can automate tasks, call multiple APIs, share memory across systems, and scale into enterprise-level AI ecosystems.
What You’ll Learn (and Build)
- Set up your AI development environment — Python 3.11+, VS Code, Docker, and API keys for GPT-4o, Hugging Face, and Azure OpenAI.
- Master Semantic Kernel — skills, plugins, kernel functions, and prompt engineering for dynamic agent behavior.
- Use MCP for interoperability — expose tools, share context, and chain agents with a universal protocol.
- Automate with n8n — trigger agents with webhooks, schedule tasks, and orchestrate multi-step workflows without writing boilerplate code.
- Implement memory and recall — store and query user context using Redis, Qdrant, or Postgres.
- Build multi-model, multi-agent systems — route tasks between GPT-4o, Claude, and Gemini for optimal performance.
- Deploy and monitor in production — containerized agents with FastAPI, Docker, secure webhooks, and API rate-limit handling.
- Scale and optimize — enterprise-ready workflows with shared memory, auto-scaling, and cost optimization strategies.
Hands-On Practice Labs
Every major chapter includes a Practice Lab — real projects you’ll build and run:
- Hello AI Agent — your first Semantic Kernel agent in VS Code.
- Personal Assistant Agent — GPT-4o + web tools for real-time answers.
- Memory-Enabled Agent — learns and remembers your preferences.
- AI Notifier — daily news summarizer with Slack and email delivery.
- Tool-Chaining Agent — connects to 3 external APIs via MCP.
- Multi-Agent Research Team — auto-generates reports with multiple specialized agents.
- Production-Deployed Agent — secure, containerized, and monitored on a VPS.
- Enterprise AI Ecosystem — fully integrated, scalable agent network.
Why This Book is Different
- Purely Practical — no fluff, just build-ready instructions.
- Up-to-Date — covers the latest Semantic Kernel, MCP, and n8n features as of 2025.
- Production-Focused — every step prepares you for real-world deployment.
- Beginner-Friendly, Expert-Level Output — even with zero AI experience, you’ll create agents that rival enterprise solutions.
Whether you’re an AI developer, automation engineer, or a complete beginner looking to break into intelligent workflows, this book gives you the skills, projects, and production mindset to build next-gen AI agents that think, act, and adapt.
If you can follow the steps, you can build the future.
Perfect for: AI developers • Workflow automation engineers • Data engineers • Beginners learning AI agents • n8n and Semantic Kernel enthusiasts • Anyone wanting to deploy real AI tools in 2025 and beyond.
"Synopsis" may belong to another edition of this title.
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