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
Error Handling and Reporting
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- JSON-RPC 2.0 Specification, JSON-RPC Working Group, 2010 - Describes the JSON-RPC 2.0 specification, including error codes and message structure, which forms the basis for protocol-level errors in MCP.
- Toolformer: Language Models That Can Use Tools, Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom, 2023 arXiv preprint arXiv:2302.04761 DOI: 10.48550/arXiv.2302.04761 - Presents a method for training language models to use external tools by learning to generate tool-use prompts and interpret their outputs, demonstrating model adaptation to tool outputs and failures.
- Pydantic Documentation: Validation, Pydantic Development Team, 2025 - Explains Pydantic's data validation capabilities, including handling
ValidationErrorand structuring validation error messages, which is useful for processing tool arguments.
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