Using Codex and MCP to connect Google Drive, GitHub, BigQuery, and analysis in one real workflow
The post Beyond Code Generation: AI for the Full Data Science Workflow appeared first on Towards Data Science.
Beyond Code Generation: AI for the Full Data Science Workflow
Towards Data Science / 3/26/2026
💬 OpinionDeveloper Stack & InfrastructureSignals & Early TrendsTools & Practical Usage
Key Points
- The article explains how to use Codex alongside MCP (Model Context Protocol) to orchestrate an end-to-end data science workflow rather than just generating code snippets.
- It demonstrates connecting common tools and data sources—Google Drive, GitHub, and BigQuery—so that analysis steps can be performed within a single integrated workflow.
- The focus is on practical workflow integration, showing how AI can support tasks across the full lifecycle of data work (from sourcing and versioning to querying and analysis).
- By moving “beyond code generation,” the post positions AI as a coordinator for multiple systems, reducing manual glue code and improving end-to-end productivity.
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