Model Context Protocol

In the rapidly evolving world of LLM agent architectures, the Model Context Protocol (MCP) has emerged as a game-changing standard for enabling seamless, dynamic interactions between AI models and external tools. This comprehensive tutorial takes you from zero knowledge to hero-level implementation of MCP Tool Discovery—the mechanism that powers intelligent, scalable agentic systems. Whether you’re building production-grade AI agents, enhancing IDEs like VS Code, or creating Claude Desktop extensions, mastering tool discovery is essential for creating truly autonomous LLM workflows.[1][7] ...

Introduction The rise of AI agents has created a fundamental challenge: how do you connect dozens of LLMs to hundreds of external tools without writing custom integrations for every combination? This is the “N×M problem”—managing connections between N models and M tools becomes exponentially complex. The Model Context Protocol (MCP) solves this by providing a standardized interface between AI systems and external capabilities. Docker’s integration with MCP takes this further by containerizing MCP servers, adding centralized management via the MCP Gateway, and enabling dynamic tool discovery. ...