This project serves as an educational resource and implementation guide for the Model Context Protocol. It provides developers with the patterns and documentation necessary to standardize how large language models interact with external systems, local data sources, and various services.
The repository focuses on facilitating the translation of technical documentation and educational materials into multiple languages. By utilizing an AI assistant integration framework, it enables the creation of localized learning resources that help developers master complex programming concepts regardless of their native language.
The project includes structured workflows for content transformation, utilizing prompt-driven context injection and schema-validated data serialization to maintain consistency and accuracy. These modular pipelines support the automated processing of technical guides to ensure global knowledge accessibility. The materials are provided as a collection of Jupyter Notebooks designed to orient developers on building and integrating tools using the protocol.
