Implement agentic systems using the full capabilities of MCP, from tool integration to deployment
Key Features
- Learn MCP fundamentals, including transports and capabilities, from the creator of mcpdotnet
- Build intelligent MCP clients and robust servers beyond API wrappers with C#, Python, and TypeScript
- Apply the 3-layer model to architect scalable LLM-based systems
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
This book is your complete guide to using MCP for building production-ready AI integrations that go far beyond simple chatbots. You'll also learn how MCP can serve as the backbone of AI software architecture, treating Resources, Prompts, and Elicitation as cohesive building blocks, not isolated features. Starting with the fundamentals, you'll explore MCP's architecture and how it solves the M×N integration problem through standardization. You'll establish connections, work with JSON-RPC, and learn capability negotiation. You'll also use SDKs in C#, Python, and TypeScript to accelerate development and reduce boilerplate. From there, you'll dive deep into Tools for model-driven actions, Prompts for messaging and control, Resources for flexible data access, Elicitation for UI input, and Sampling to enable the client to act as an LLM provider. Moving from theory to practice, you'll build secure MCP servers with proper error handling, logging, and authentication. You'll implement clients that safely expose capabilities while defending against malicious servers. The book also covers deployment strategies, enterprise patterns, and integration with tools like GitHub Copilot, Claude, and Cursor. By the end, you'll be ready to design and operate scalable, agentic systems with MCP at their core.
What you will learn
- Connect AI models to external systems using MCP
- Learn MCP Tools, Prompts, Resources, Elicitation, and Sampling
- Build MCP server using SDKs with logging, error handling, and security
- Implement secure MCP clients to protect users from malicious servers
- Design MCP architectures from simple integrations to multi-agent systems
- Integrate MCP with tools like GitHub Copilot, Claude, and Cursor
- Manage authentication, deployment, and operations for enterprise use
- Apply safeguards to block command injection and prompt attacks
Who this book is for
This book is for software engineers and architects who want to move beyond the hype around MCP and gain deep, practical skills. Whether you're building AI-powered applications or designing system architectures, you'll learn to create production-ready integrations between AI models and systems. Readers should have basic familiarity with LLM APIs or SDKs and experience with C#, Python, or TypeScript.
