How do I make my AI coding agent verify code automatically?

Install CodeLoop as an MCP server with `npx codeloop init`. Cursor and Claude Code will then call codeloop_verify after every change and codeloop_gate_check before declaring done.

Does this work with both Cursor and Claude Code?

Yes. `npx codeloop init --global` writes the MCP entry for both, plus the global rules so every session triggers verification automatically.

How does CodeLoop avoid the LLM token tax other verifiers add?

CodeLoop is fully deterministic — lint, build, tests, screenshot capture, pixel diff. No model calls. Your token spend depends only on how much the calling agent edits, not on how many verify cycles it runs.

How to Verify AI-Generated Code Automatically (2026 Guide)

AI coding agents in Cursor and Claude Code now write 80%+ of the code in many shops. The bottleneck has shifted from typing speed to verification: how do you trust the agent's output without manually testing every change?

This guide walks through the working pattern in 2026.

The pattern: verify → diagnose → fix → gate-check

The reliable loop has four steps:

Verify — after every change, run the build, tests, lint, and capture a screenshot of the affected screen.

Diagnose — when verify fails, classify the failures into structured issues with concrete repair tasks.

Fix — the agent edits files based on the diagnosed tasks.

Gate-check — before declaring done, compute a confidence score across build, tests, lint, screenshots, and design diff. Only ≥ 94% allows the agent to claim completion.

The trick is making the agent run this loop without you reminding it.

Setting it up in 90 seconds

Install CodeLoop, the open-source MCP server purpose-built for this loop:

npx codeloop auth

cd your-project

npx codeloop init

That writes:

- ~/.cursor/mcp.json and ~/.claude.json so Cursor and Claude Code know the server exists.

- ~/.cursor/codeloop-user-rule.md (paste into Cursor → Settings → Rules → User Rules) and ~/.claude/CLAUDE.md (auto-injected) so the agents know to call codeloop_verify after every change.

- ./.codeloop/config.json for the project-specific stack detection.

Verify with npx codeloop doctor — every required line should be green.

What "automatic" actually means

Once the user rule is in place, every Cursor or Claude Code session calls these tools without you typing them:

- codeloop_verify after each agent edit.

- codeloop_diagnose on failure.

- codeloop_capture_screenshot + codeloop_visual_review for UI changes.

- codeloop_design_compare if designs/ or .codeloop/figma.json exists.

- codeloop_gate_check before declaring done.

The agent loops fix → verify until codeloop_gate_check returns ready_for_review with confidence ≥ 94%. You see the final passing state and an evidence-backed dev report — never the failed intermediate runs.

Why "zero LLM cost" matters

CodeLoop is deterministic. It runs the same lint / build / test / pixel-diff your CI runs. It never spawns its own model calls, which means:

- Your token spend is independent of how many verify cycles the agent runs.

- The verifier doesn't fail randomly because of model regression.

- Your code never leaves your machine for the verification step.

What about CI?

The same MCP tools are exposed via a CLI (npx codeloop verify) and a GitHub Action. Your PRs get the same gate-check the local agent does, so a "ready_for_review" agent claim and a green PR check mean the same thing.