Demonstrates the Model Context Protocol (MCP) for AI assistants to interact with external tools and data sources.
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This educational demo provides a hands-on guide to understanding the Model Context Protocol (MCP), a vital standard for enabling AI assistants to connect with external tools and data. Through practical examples, it illuminates the core concepts of defining, listing, and calling tools, the underlying JSON-RPC 2.0 request/response format, and various transport methods like stdio and HTTP. Ideal for developers, it covers everything from setting up local and remote MCP servers and clients using TypeScript to real-world testing with curl and programmatic clients, ensuring a comprehensive learning experience.
Key Features
01Explains JSON-RPC 2.0 request/response format
02Covers stdio (local) and HTTP (remote) communication transports
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04Teaches MCP Protocol Basics: tool definition, listing, and calling
05Guides through TypeScript development of MCP servers/clients
06Demonstrates error handling within the MCP framework
Use Cases
01Learning the Model Context Protocol for AI tool integration
02Understanding JSON-RPC 2.0 for building API interactions
03Developing and testing custom MCP servers and clients
04Implementing robust error handling in AI-tool communication
