"Model Context Protocol (MCP) is a technology that enables AI models to connect with external tools and data sources (such as GitHub, Slack, databases, and documentation systems). In this article, I want to explore my top 7 favorite MCPs you can use in your design process. I will cover not only benefits but also limitations of the each MCP so you will have a clear idea about what you can & cannot do with it."
"As the name suggests, the main objective of context7 is to create a proper context for AI engines. This tool acts as a source of truth in the design process. It pulls all up-to-date documentation & code examples into AI coding engines like Cursor. This helps avoid any inconsistency or mismatch with product requirements, as the AI engine will have a proper context for what and why something should be built."
Model Context Protocol (MCP) enables AI models to connect with external tools and data sources such as GitHub, Slack, databases, and documentation systems. MCP supplies relevant context to AI engines so generated outputs align with current code, documentation, and product requirements. Multiple MCP implementations can be applied in a design process, each offering distinct capabilities and trade-offs. context7 creates product context for AI coding tools by acting as a source of truth and pulling up-to-date documentation & code examples into coding engines like Cursor. Providing that context helps avoid inconsistencies or mismatches with product requirements during development.
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