mcp-crash-course and model-context-protocol-resources

These two tools are complements, with the crash course providing structured learning with project-based branches for Streamable-HTTP, LangChain, and Docker, while the resources offer practical guides, client, and server implementations for deeper exploration of the Model Context Protocol.

Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 15/25
Stars: 142
Forks: 125
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: 270
Forks: 27
Downloads:
Commits (30d): 0
Language:
License: Apache-2.0
No Package No Dependents
Stale 6m No Package No Dependents

About mcp-crash-course

emarco177/mcp-crash-course

Hands-on crash course for the Model Context Protocol (MCP) with project-based branches on Streamable-HTTP, LangChain adapters, and Docker.

Implements MCP through multiple transport mechanisms including Server-Sent Events (SSE) and stdio, with specialized branches teaching integration patterns for LangChain adapters and FastMCP 2.0 prompt handling. The learning structure uses chronologically-ordered Git commits within feature branches, allowing developers to trace architectural decisions step-by-step from initial server setup through production containerization with Docker.

About model-context-protocol-resources

cyanheads/model-context-protocol-resources

Exploring the Model Context Protocol (MCP) through practical guides, clients, and servers I've built while learning about this new protocol.

Based on the README, here's a technical summary: Includes 12+ production MCP server implementations (filesystem, Git, GitHub, PubMed, Perplexity, Obsidian) alongside TypeScript/Python client templates and multi-SDK support across TypeScript, Python, Kotlin, Java, and C#. The project provides structured guides for building both MCP clients and servers, establishing a standardized transport layer for AI agents to access external tools and data sources. Targets developers building agentic LLM applications requiring modular, extensible capability integration through the open MCP specification.

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