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Driver adds a context layer on top of a codebase that works for both developers and AI tools. It converts scattered files and modules into structured documentation that AI assistants can reliably use.
Driver analyzes a project and builds a coherent view of its architecture, modules, and dependencies. This helps developers ramp up faster on unfamiliar repositories, while AI assistants get accurate, up-to-date context instead of fragmented prompts.
The generated documentation is delivered through an MCP interface to popular AI coding tools, including Cursor, Claude Code, GitHub Copilot, and others. This reduces “blind spots” in autocomplete, code generation, and reviews because assistants can reference the real project structure, not just the currently open file.
Driver is especially useful for big or long-lived projects where missing context can cost hours or days. It helps teams maintain a shared understanding of the system, rely less on tribal knowledge, and make day-to-day work with the codebase more predictable and transparent.