TestivAI

Name: TestivAI
Author: testivai

作者：testivai版本 0.9.2i★ –i在你的电脑上运行

注册名称ai.testiv/mcp

安装

概览

作者提供的说明（英文原文）

Local-first visual regression for AI agents: verdicts, diff images, explain_snapshot. No API key.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 其他

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
注册中心没有列出需要填写的密钥。

你需要

npm已安装 Node.js（用于 npx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "testiv": {
      "command": "npx",
      "args": [
        "-y",
        "@testivai/mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add testiv -- npx -y @testivai/mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "testiv": {
      "command": "npx",
      "args": [
        "-y",
        "@testivai/mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "testiv": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@testivai/mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

✓ 通过
作者与仓库一致
注册名称已通过域名 testiv.ai 验证（注册中心会核实域名所有权）
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

星标数多于此分类中其他 32461 个服务器的 0%
发布到注册中心的时间比此分类中其他 32461 个服务器的 94% 更新
基础检查结果等于或优于此分类中其他 32461 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

TestivAI 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（0.9.2）于前天进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它？

同一分类中有：Spec Driven Development, Remote Desktop Commander, dotnet-mcp

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者：formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新

安装

Remote Desktop Commander

作者：desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新

安装

dotnet-mcp

作者：Skymly

MCP server for .NET symbols, XAML, source generators, and restricted workspace edit

在你的电脑上运行今天更新

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

@testivai/mcp

MCP (Model Context Protocol) server that gives AI coding agents eyes on your visual regression results. The agent changes UI code, runs your test suite, then uses these tools to find out what actually changed on screen — and whether it is a real change, likely render noise, or a case the DOM and style signals cannot settle.

Tools

Tool	What it does
`get_visual_results`	Reads `visual-report/results.json`; when two or more snapshots share one environment change, opens with one line saying so and how many of them are rendering drift; then returns a one-line verdict per snapshot: unhealthy capture (a web font or stylesheet failed to load in the current capture or the baseline, named in the verdict: a glitch of the capture or a broken asset, never noise and never to be approved as a baseline; said before any other reading) / passed (an auto-passed diff says which configured criterion passed it) / size changed (the current capture's dimensions differ from the baseline's: a taller or shorter page is read with the DOM summary and the page shift, and with an identical DOM it is the same content laid out differently, not content added; a width change is the viewport or device scale, not the page; every padded pixel counts as changed, so it is never passed and never noise) / rendering drift (the DOM and computed styles both match and the environment the snapshot was captured in changed since the baseline: a browser build, OS or distro, device scale or capture method, named in the verdict; the machine changed, not the page, so it is never called noise) / likely render noise (the DOM and computed styles both match and the diff is small and scattered; still not proof) / concentrated in one area or large (the DOM and computed styles match, but every diff region fits in a box covering at most a third of the page, or over 1% of pixels differ: a bad capture or a change the style check does not cover, such as size, overflow, transform or an image, so compare the images before approving) / style-only change (identical DOM, different computed styles: a real change) / structural change (with the DOM summary) / styles not compared (identical DOM, style check unavailable: could be render noise or a stylesheet-only change, so compare the images before approving). Snapshots that share an identical signal (style-only change on the same elements, the same page shift, identical DOM with styles not compared, a large spread-out diff, likely render noise) are grouped first; a diff concentrated in one area, or an unhealthy capture, is never grouped. Each missing baseline (committed, but no capture this run) gets its own line (several share one verdict line, so a partial run stays short), with nothing to approve: an intended removal deletes the baseline directory. It ends with the paths to open the HTML report and each diff image
`explain_snapshot`	Layered evidence for one snapshot: pixel regions and the shape of the diff (`layers.pixel.shape`: scattered, concentrated or large), element attribution (which selectors shifted vs changed, whole-page shift), the DOM/style signal, the capture environment (`layers.environment`: what changed since the baseline, the rendering changes worded, and whether the diff is rendering drift), the capture health (`layers.health`: what failed to load in each capture and which side is unhealthy), and interpretation guidance; for a missing baseline, status `missing`, the committed baseline files and what to check instead
`get_report`	The raw `results.json` payload, for agents that parse structured data
`get_diff` (alias `get_snapshot_diff`)	Returns the baseline, current, and diff images for one snapshot so the agent can see the change: the full page downscaled to fit model context (it shows where the changes are), then, when it had to be downscaled, each changed region cropped at native scale with 32 px around it and as wide as the page (up to 1280 px), so text, wrapping and clipping stay readable on a tall full-page capture (up to 3 crops per call, each at most 1280×1024 px and 2,000,000 px in all; nearby regions share a crop, changes come before shifts, a wider area is sampled at 1/2 scale or smaller, a taller one shows its top rows, and after a size change each capture is cut to its own bounds). `region` (an index the response lists), or `y` and `height` (a full-width band), return only that crop; for a missing baseline, the committed baseline image only
`list_baselines`	Lists the committed baselines under `.testivai/baselines/`
`approve_snapshot` / `approve_all`	Promote reviewed captures to committed baselines (same as `testivai approve`), only after a human confirms

The server also ships two prompts. review-visual-changes walks the agent through a full review: summary, explain_snapshot per change, diff images when the evidence is ambiguous, and a recommendation per snapshot. triage-visual-diff (optional snapshot and intent arguments) sorts each diff, and each missing baseline, into glitch, intended change, bug or possible bug, with the evidence and a next step; a changed DOM or changed computed styles is never a glitch, and neither is a missing baseline. The same rules run in CI with the testivai/testivai-oss/review@v1 action.

Approval is a human decision

approve_snapshot and approve_all exist so a human who has looked at a diff can say "approve it" in the conversation and have the agent carry it out. They are not for the agent to decide on its own: approving rewrites what "correct" means, so an agent that approves its own change can launder a regression into the baseline. Both tool descriptions, the review-visual-changes prompt, and every get_visual_results response say so. After approving, commit .testivai/baselines/.

In Claude Code the client enforces this: both approve tools are marked anthropic/requiresUserInteraction, so Claude Code asks you on every approve call, even in auto-approving permission modes. To turn that off, start the server with --no-approval-prompt or set "mcpApprovalPrompt": false in .testivai/config.json (the flag wins); the approve tools then follow your client's own permission settings. Walkthrough: Review and approve in Claude Code.

The other approval paths stay available: npx testivai approve locally, or a /testivai approve comment on the pull request.

Setup

Claude Code

claude mcp add testivai -- npx -y @testivai/mcp

Cursor / other MCP clients

// .cursor/mcp.json (or your client's equivalent)

{ "mcpServers": { "testivai": { "command": "npx", "args": ["-y", "@testivai/mcp"] } } }

The server reads the project from its working directory (pass --root to override) and respects reportDir from .testivai/config.json.

Typical agent flow

Agent edits UI code.
Agent runs npx playwright test (the TestivAI reporter captures + diffs).
Agent calls get_visual_results and sees, for example, homepage: changed (4.20% pixels differ) and the DOM changed (2 added, 1 removed, 0 attribute changes) — a real structural change; confirm it is intended before approving.
Agent calls explain_snapshot homepage for the evidence, and get_diff homepage to look at the images (the full page, then the changed regions at native scale), then confirms the change matches the task (or fixes its own regression).
Agent reports to the human: what changed, whether it looks intended, and which snapshots need approval. If the human says to approve, the agent calls approve_snapshot; otherwise the human approves with npx testivai approve or /testivai approve on the PR.

Local mode only — no account, no API key, nothing leaves the machine.

Full integration guide (instructions-file level, MCP level, zero-test-suite apps, real transcript): docs/guides/ai-agents.md