Building a Debugging Agent Harness at Uber - Kriti Dangi

Join us at AGNTCon + MCPCon NA 2026 https://hubs.la/Q04gbXLb0 MCP-Powered Crash Investigation: How 11 MCP Servers Help an AI Agent Debug Production Issues at Uber - Kriti Dangi, Uber Debugging eats 42% of developer time — $300B lost globally every year. On an average, fixing an issue takes 15 days. Debug Assist does it in 30 minutes — issue alert to validated, reviewable PR. Most AI debugging tools stop at root cause analysis. Debug Assist goes much further: it writes a fix, validates it in a loop till correct, and creates the PR. Example, It caught a crash at 5% rollout, landed the fix the same day — preventing it from reaching thousands of users. Built on LangGraph with 11 MCP servers, 5 plugins, and parallel subagents: Sourcegraph for code search, crash analytics, Jira, feature flags, Jaeger, and logging — all one protocol. Debug Assist even works on user-reported bugs which have minimal information attached. A user complained of battery drain, and Debug Assist traced it to a hot-looping code path, producing an RCA from behavioral evidence alone. Domain knowledge lives in markdown skill files in a plugin marketplace — any developer can contribute fix patterns with no code, no redeployment. We'll share how we built this from ground up, scaled to 5,000 RCAs/month across 6 languages, the challenges we hit, and how we improved the acceptance rate from 5% to 30%.