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Chapter 38: Building Custom MCP Servers

Chapter 37 taught you to use MCP servers. Now you'll build them. Custom MCP servers are how you extend AI agents with capabilities that don't exist yet—connecting to your company's internal APIs, wrapping proprietary data sources, or encoding domain expertise that no public server provides.

Building MCP servers is where agent development becomes genuinely creative. You're not just using AI; you're expanding what AI can do. Every MCP server you create becomes a reusable capability that any MCP-compatible agent can leverage. This is the "composable intelligence" vision in practice.

This chapter takes you from "hello world" MCP server to production-ready implementations. You'll build servers in Python using the official SDK, understanding both the protocol mechanics and the design patterns that make servers robust and maintainable.

What You'll Learn​

By the end of this chapter, you'll be able to:

  • Scaffold MCP servers: Use the official Python SDK to create server projects with proper structure
  • Implement tools: Define tool schemas, handle invocations, validate parameters, and return results
  • Expose resources: Provide data access through MCP's resource abstraction with proper URIs
  • Create prompt templates: Bundle domain expertise into reusable prompts that guide agent behavior
  • Handle authentication: Secure servers that access protected resources or APIs
  • Test MCP servers: Validate server behavior with unit tests and integration tests
  • Deploy servers: Package servers for distribution and configure them in client applications

Chapter Structure​

  1. MCP Server Architecture — SDK structure, lifecycle hooks, and the request/response flow
  2. Building Your First Server — Scaffolding, basic tool implementation, and local testing
  3. Advanced Tool Patterns — Complex parameters, streaming results, error handling, and timeouts
  4. Resource Implementation — URI schemes, content types, and dynamic resource generation
  5. Prompt Templates — Encoding expertise, parameterized prompts, and prompt composition
  6. Authentication & Security — API key handling, OAuth flows, and secure credential storage
  7. Testing & Deployment — Unit testing tools, integration testing with clients, packaging for distribution
  8. Capstone: Domain-Specific Server — Spec-driven implementation of an MCP server for a real-world domain (e.g., project management, CRM, or analytics)

Prerequisites​

  • Chapter 37: MCP Fundamentals (protocol understanding)
  • Part 5: Python Fundamentals (functions, classes, async/await)
  • Part 4: SDD-RI Fundamentals (specification-driven workflow)