I also built something similar to solve this, but more aimed at inspecting the impact of changes to a concept - think a vertical slice or domain, or even a feature. Often the same thing might be referred to by similar, but slightly different names, or separate pieces of the codebase might not immediately look related when they do share dependencies. So symbols, phrases, and words are attached to concepts for either LLM-based or user-based querying via MCP.

An indexer crawls the codebase and maps slices of code to concepts, then groups related concepts. You can inspect a concept to see things related to it, or ask about the impact of a change and see second-order changes required - things not so easy to see that are related by basic symbol linking (although it does use symbol linking - it heavily relies on Roslyn, since it's all C# focused).

It also returns confidence scores with everything, which adjust based on a dozen or so factors like whether the user defined the concept or the concept was auto-generated during the code crawl. Low confidence score === fall back to grep.

It was a super fun project and ended up being very useful, as much for people as the LLM. But, I'm not convinced it is materially better than grep in some ways and just haven't had the time to really focus on improving it.