Getting Started with Model Context Protocol (MCP)
Chapter 1: Architecture and Fundamentals
The MCP Specification Overview
Client-Host-Server Topology
JSON-RPC Message Structure
Transport Mechanisms: Stdio and SSE
Capabilities Negotiation
Hands-on Practice: Environment Setup
Chapter 2: Defining Resources and Prompts
Concept of Resources in MCP
URI Schemes and Patterns
Implementing Synchronous Resource Reads
Resource Subscriptions and Notifications
Structuring Prompts
Hands-on Practice: Building a File Reader Server
Chapter 3: Implementing Tools and Logic
Tool Definition Schema
Input Validation with Pydantic
Executing External API Calls
Error Handling and Reporting
Designing Computed Resources
Hands-on Practice: Creating a Database Tool
Chapter 4: Debugging and Client Integration
Using the MCP Inspector
Analyzing Log Output
Configuration for Claude Desktop
Managing Environment Variables
Handling Connection Lifecycles
Hands-on Practice: End-to-End Integration
Input Validation with Pydantic
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- Pydantic Documentation, Samuel Colvin and Pydantic contributors, 2024 - The authoritative resource for understanding Pydantic's features, including data model definition, type validation, custom validators, and JSON Schema generation.
- JSON Schema, IETF and JSON Schema community, 2020 - Provides the standard for declaring the structure and validation constraints of JSON data, foundational to how Pydantic models are serialized for LLM tools.
- FastAPI and Pydantic Cookbook, Alessandro Giusti, 2024 (Packt Publishing) - Illustrates how Pydantic is used in practical applications, particularly within API development frameworks like FastAPI, for defining request schemas, performing validation, and generating OpenAPI (JSON) Schema.
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