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MCP Fundamentals for Engineers

Master the Model Context Protocol (MCP). Build standard servers and clients from scratch and solve the M×N integration nightmare once and for all.

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Taught by an engineer who has shipped this

  • ISO 27001

    Led the engineering work behind the certification of a regulated EU platform.

  • Series A platform

    Architected the case-management product that became the business a €11.6M round was raised on.

  • 3x faster deploys

    Cut time-to-deploy by migrating to Kubernetes on GCP with deploy-on-merge.

Every new AI integration means more glue code: schemas, dispatchers, parsers. MCP fixes this. Build MCP servers and clients from scratch: tools, resources, prompts, multi-server routing. Go from 200 lines of boilerplate per integration to zero.

Build MCP servers and clients from scratch. No more glue code.

What you'll ship

Real projects, not toy demos.

  • Understand why MCP exists and the M×N integration problem it solves
  • Build an MCP server with tools, resources, and prompts using FastMCP
  • Build MCP clients that auto-discover and call server capabilities
  • Connect a full chat UI to MCP servers with LLM integration
  • Design multi-server architectures with config-driven routing

What you'll learn

You finish able to:

  • Understand the M×N integration problem and how MCP solves it
  • Build MCP servers with tools, resources, and prompts using FastMCP
  • Build MCP clients that auto-discover server capabilities
  • Connect LLM-powered chat UIs to MCP servers
  • Design multi-server architectures with config-driven routing

Curriculum

From Zero Integrations to Multi-server MCP.

  1. 01

    Why MCP exists

    Understand the integration nightmare that MCP solves. See the M×N problem, feel the pain, and discover the protocol that fixes it.

  2. 02

    MCP architecture

    Learn the three roles (Host, Client, Server), three capabilities (Tools, Resources, Prompts), and transport protocols that make MCP work.

  3. 03

    Feel the pain

    Build tool integrations the manual way with hand-written schemas, dispatchers, and glue code. Feel the boilerplate so the MCP relief hits harder.

  4. 04

    Your first MCP Server

    Build an MCP server with FastMCP, test it with the MCP Inspector, and connect your first client. Watch the boilerplate vanish.

  5. 05

    The complete picture

    Build a full chat client with LLM integration, add MCP resources for read-only data, and prompts for workflow templates.

  6. 06

    Multi-server architecture

    Connect to multiple MCP servers simultaneously. Add new data sources with a single line in a config file.

Who it's for

Is this for you?

AI engineers

You are writing the same tool schemas and dispatchers for every new integration. There has to be a better way.

Backend developers

You want to expose your APIs to AI apps but do not want to maintain custom integrations for each one.

Technical leads

Your team is building AI features and you need a standard protocol instead of custom glue code everywhere.

FAQ

Common questions.

  • Do I need to know LangChain?

    No. We use pure Python and LiteLLM. No frameworks.

  • What LLM provider do I need?

    Any provider that supports function calling. LiteLLM handles OpenAI, Anthropic, Google AI Studio (free tier), and more.

  • Should I take Building AI Agents first?

    Yes. This workshop assumes you understand tool calling and agent loops. Building AI Agents covers those foundations.

  • How long does the workshop take?

    About 7 hours. Most people finish in 2 sessions over a weekend.