From the course: OpenAI Codex 101: From Idea to Deployed App

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Extend Codex with MCP

Extend Codex with MCP - OpenAI Codex Tutorial

From the course: OpenAI Codex 101: From Idea to Deployed App

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Extend Codex with MCP

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Every task you've given Codex so far, it handled, using what it learned during pre-training. For Flask basics, that works fine. But training data has a shelf life, libraries update, APIs change, and best practices evolve. MCP, or Model Context Protocol, solves this by connecting Codex to live data sources. Instead of guessing, Codex can look things up in real-time. You're going to connect Codex to a tool called Context 7, which gives it access to current documentation for thousands of libraries, including Flask. Let's navigate to context7.com so you can see the page. It's up-to-date docs for LLMs and AI code editors like Codex. Codex stores MCP configuration in config.toml alongside other Codex configuration settings. Let's see if Codex can help us set up this MCP server. There are commands you can send to Codex like slash plan. Slash plan is a command that triggers plan mode, which instructs Codex to propose a detailed a step-by-step execution plan before it makes any coding changes.…

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