Anthropic
Self-paced
This course covers the technical implementation of MCP servers and clients, from basic message passing to production deployment strategies. You'll learn how MCP enables language models like Claude to interact with external tools and data sources through standardized protocols, transports, and message formats.
This course is for engineers building production MCP servers who need to understand the protocol's advanced capabilities. It requires a basic understanding of MCP servers and clients, as well as familiarity with async programming patterns.
The course is divided into two main sections. The first section covers the core MCP features, including how to implement MCP servers with tool functions, logging, and progress notifications. It also explores handling bidirectional communication between MCP clients and servers, configuring file system access using the roots permission model, and working with both stdio and HTTP transports for local and remote deployments. The second section focuses on transports and communication, diving into the JSON message protocol, the STDIO transport for local development, and the complexities of StreamableHTTP, including when to sacrifice features for scalability.
Anthropic is a leading AI research company that has developed advanced language models like Claude. This course is designed to provide engineers with a deep understanding of the technical implementation of the Model Context Protocol (MCP), which is a key component of Anthropic's AI systems. By taking this course, you'll gain valuable insights into how to build production-ready MCP servers and clients, enabling you to integrate Anthropic's AI capabilities into your own applications.
After completing this course, you'll be able to implement MCP servers with advanced features like sampling, notifications, and transport configurations. This knowledge will allow you to build more powerful and scalable applications that leverage Anthropic's language models and other AI capabilities. You'll be equipped to deploy MCP servers in production environments, troubleshoot common issues, and ensure secure and efficient communication between your applications and Anthropic's AI services.
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