An AI agent for QA, built for the AI code era.
Sniffer captures every bug your team ships, diagnoses the root cause across the full stack, opens a pull request with the fix, and writes the regression test that keeps it from coming back. One agent, four moves, end to end.
A quick orientation.
AI code generation made shipping 10x faster. The work that didn't get faster is bug reproduction, root-cause analysis, and regression coverage. Sniffer closes that gap.
Sniffer plugs into your IDE through MCP (Cursor, Claude Code, Windsurf) and into your runtime through lightweight capture. When a defect is detected, the agent collects the full context (browser state, network, logs, traces), reasons across the stack to identify the root cause, opens a pull request with the fix, and adds a regression test before closing the loop.
It's how teams using AI-generated code keep shipping fast without burning quality.
Capture. Diagnose. Fix. Prevent.
Sniffer is built around a four-step loop. Each step is automated, observable, and reviewable, so the agent does the heavy lifting and engineers stay in control of every change.
- C
Capture
Full-context capture of every defect: browser and app state, network calls, console output, traces, and the steps that led to the bug. No more 'works on my machine'.
- D
Diagnose
The agent reasons across frontend, backend, and data to identify the actual root cause, not just the symptom. Findings are explained in plain English with the evidence linked.
- F
Fix
Sniffer opens a pull request with the proposed fix. Engineers review, edit, and merge on their normal workflow. The agent proposes; humans ship.
- P
Prevent
Every fix lands with a regression test that catches the bug if it ever returns. Quality compounds across releases instead of decaying.
The full bug lifecycle, on autopilot.
Plugs into the tools your engineers already use. No new dashboards to babysit, no new processes to learn.
MCP-native IDE integration
Connects to Cursor, Claude Code, and Windsurf through Model Context Protocol. Bugs surface inside the IDE the engineer is already in.
Full-stack defect capture
Browser state, network requests, console output, server traces, and reproduction steps captured in one bundle the agent can actually reason over.
Root-cause diagnosis
The agent walks frontend, backend, and data paths to pinpoint the underlying cause, with the evidence trail attached for human review.
Auto-generated pull requests
Fixes ship as standard PRs against your repo. Reviewable diffs, normal CI, normal merge flow. Engineers stay in the driver's seat.
Regression test generation
Every fix lands with a test that locks the behavior in. Coverage compounds release after release.
Production-traffic-to-tests
Real user flows captured in production become regression suites. Coverage that mirrors what users actually do, not what someone guessed.
Built for the people who carry the risk.
- Engineering teams shipping AI-generated code at velocity
- QA leaders trying to keep coverage from collapsing under release pressure
- Platform teams modernizing legacy code where regression risk is the blocker
- Regulated industries that need an audit trail for every fix
What teams actually get.
- Mean time to repair measured in hours, not days
- Coverage that grows automatically with every release
- Defects caught and fixed before customers escalate
- An audit trail for every diagnosis, fix, and regression test
Want to see Sniffer on your stack?
Get a walkthrough on your codebase, your APIs, your tests, or your candidate pipeline. We bring the agent. You bring the hard problem.