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MCP Tutorial

10 free lessons, in the order we teach them in class: start at lesson 1 and work down. Every lesson has an analogy, a diagram, code you can run or copy, a quick quiz and an FAQ.

Start lesson 1 Learn it in class: free demo
  • 10Lessons
  • 1Modules
  • ~2 hReading time
  • FreeAlways

01Model Context Protocol

  1. What is MCP? The Model Context Protocol Explained for BeginnersWhat is MCP? The Model Context Protocol explained: hosts, clients, servers, tools, stateless JSON-RPC in spec 2026-07-28, and a Python tools/call simulation.
  2. Why MCP Was Created: Problems Before Model Context ProtocolWhy was MCP created? See the glue-code, drift and discovery problems AI apps faced before 2024, how MCP fixed them, and how the spec changed through 2026.
  3. MCP Architecture: Hosts, Clients, Servers and TransportsMCP architecture in depth: host, client and server roles, the data and transport layers, stateless requests in spec 2026-07-28, stdio vs Streamable HTTP.
  4. MCP Tools, Resources and Prompts: The Three Server PrimitivesMCP tools, resources and prompts explained field by field: schemas, annotations, structured output, URI templates, prompt arguments, plus runnable Python demos.
  5. MCP vs REST API: Differences, Examples and When to Use EachMCP vs REST API compared on discovery, endpoints, errors, auth and caching, with a runnable Python wrapper that turns a REST API into MCP tools.
  6. MCP vs Function Calling: How They Differ and Work TogetherMCP vs function calling: function calling is how a model asks for a tool, MCP is how the app reaches it. See the full loop with runnable Python code.
  7. Build an MCP Server in Python with MCPServer (SDK 2.x Guide)Build an MCP server in Python with the official SDK 2.x: MCPServer, typed tools, ToolError, resources, prompts, progress, stdio and Streamable HTTP, plus tests.
  8. Build an MCP Client in Python: Connect Servers to an LLMBuild an MCP client in Python with SDK 2.x: connect over stdio or HTTP, merge tools from many servers, gate risky calls, and drive an LLM tool loop.
  9. MCP Security Best Practices: Threats, Auth and Safe DefaultsMCP security best practices: tool poisoning, rug pulls, prompt injection, token audience, no passthrough, local server risks, with runnable Python checks.
  10. MCP Tool Overload: How to Keep AI Agents Accurate with Many ToolsToo many MCP tools hurt agent accuracy and cost. Measure the token load, then fix it with task-level tools, tool profiles and dynamic tool retrieval in Python.
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