Model Context Protocol: Build Production-Ready AI Integrations

The complete guide

The course →

The whole playbook in writing — 5 chapters, 28 sections, diagrams included. Free to read, no account needed. The hands-on sessions, exercises and practice live inside the course.

Chapters

  1. 1. MCP Foundations

    Understand what MCP is, why it exists, and where it fits in the AI application stack.

    Why MCP Exists · MCP Mental Model · Anatomy of an MCP Interaction · When to Use MCP

  2. 2. Building Your First MCP Server

    Build a working MCP server that exposes useful tools, resources, and prompts.

    Development Environment and SDK Setup · Your First MCP Tool · Designing Tool Interfaces · Exposing Resources · Prompts and Reusable Workflows · Mini Project: Personal Knowledge MCP Server

  3. 3. Context, Data, and Agent Workflows

    Design MCP servers that provide the right context without overwhelming or leaking data.

    Context Engineering for MCP · Connecting MCP to External APIs · MCP for Databases and Internal Systems · Multi-Step Agent Workflows · Error Handling and Recovery · Mini Project: CRM or Ticketing MCP Server

  4. 4. Security, Permissions, and Trust

    Build MCP systems that respect user intent, protect credentials, and reduce unsafe model actions.

    MCP Threat Model · Authentication and Authorization · Permission Boundaries and Human-in-the-Loop Controls · Prompt Injection and Untrusted Data · Logging, Auditing, and Compliance · Security Review Workshop

  5. 5. Production MCP Systems

    Deploy, operate, and evolve MCP servers as reliable production infrastructure.

    Local vs Remote MCP Servers · Testing MCP Servers · Observability and Debugging · Versioning and Backward Compatibility · Deployment and Operations · Final Capstone: Production-Ready MCP Integration

Ready to actually do the work?

The guide gives you the map. The course gives you the workspace — practice, tools and feedback on every session.

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