To enable AI tools to process information stored in existing software systems or databases, that data must reach the language model’s context window. There are only two ways to achieve this: (1) include it directly in the prompt, or (2) provide it as the result of a call to an LLM tool/function.
The Model Context Protocol (MCP) offers a standardized pattern for discovering, grouping, and enabling sets of AI tools that language models can access. However, most traditional web services are not well-suited for agentic workflows. To support true agentic patterns with your existing systems, you need an MCP server.MCP is emerging as the new standard API for large language models.
This training will jumpstart your journey toward designing and implementing an MCP server for your custom system or database.