Detrix is an MCP server that gives AI coding agents (Claude Code, Cursor, Windsurf) a debugger they can control directly. The agent sets observation points on variables in a running process, captures values at runtime, and queries results when ready — no restarts, no code changes at debug time, no print statements. Here's what that looks like in Claude Code:
I didn't tell it what to observe. It read the source, picked the variables, watched them live, and found the root cause.Under the hood it's DAP logpoints — most debuggers can already evaluate expressions without stopping the target. Detrix exposes that over MCP. Pull-based: nothing streams into context, the agent queries when ready. Overhead is near-zero — logpoints are non-breaking, no pauses, configurable throttling on hot paths. Expression safety layer with allow/block lists prevents accidental exposure of secrets or API keys. Works locally and remotely — Detrix server runs alongside your service in Docker or on a remote host, so the agent on your laptop observes a process running in the cloud. Python (debugpy), Go (Delve), Rust (lldb-dap). Ships with a Claude Code skill that makes Claude reach for Detrix before suggesting print statements. Built this after debugging a trading bot migration where the broker silently changed their price format — the add-prints-restart-wait loop on timing-sensitive code is what Detrix eliminates. 13 Rust crates, 2,300+ tests. MIT licensed. Docker demo with video in `examples/docker-demo/`. Would love feedback on the DAP approach — are there edge cases in your stack where this would break down? |