Stop grepping. Start querying. I've been using Claude Code for over a year to build Code-Pathfinder. It's incredible for prototyping and exploring design choices. But I kept hitting the same problem. Every conversation, I'd watch the LLM (Agent) grep through files, read entire modules, hunt for needle in the haystack. I'd lose confidence in responses. Precision would drop when context windows grew. I'd correct obvious things: 🎙️"no, that function is called by these 12 places" or 🎙️"this import resolves here" or 🎙️"can you cross check where this method are invoked" 🎙️ "Are you sure this class contains this abc methods"? The agents was searching when it should have been knowing or atleast could have been accessible. So, I built something for myself. An MCP server that exposes Code-Pathfinder's indexed call graphs directly to AI agents. No more grepping. No more reading full files. Just instant queries: 👉who calls this? 👉what does this depend on? 👉where does this import go? The shift was immediate. Conversations went from "let me search..." to "here's exactly what you asked." More trust. Fewer corrections. Faster iterations. Bonus: Working with microservices? Configure multiple Pathfinder instances - one for your Python SDK, one for your gRPC server, one for your BFF layer. Query across all repos in a single prompt. Your AI agent gets the full picture without grep-ing all the way through the repo. I used it for weeks, refined it, then realized: if this fixed my workflow, maybe it should help with similar python projects. Today I'm open sourcing it: codepathfinder.dev/blog/mcp-…