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Periscope MCP

作者:segentic-lab版本 0.10.4i★ –i–
注册名称io.github.segentic-lab/periscope-mcp

安装

概览

作者提供的说明(英文原文)

Web-app QA for AI agents: 73 Playwright tools — auth, E2E, a11y/SEO/GEO, Web Vitals + Lighthouse

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。

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: –
  • 传输方式:
  • 分类: 营销与社交媒体

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。

作者没有在注册中心列出安装信息。请查看下方作者的 README。

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7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 segentic-lab 验证,该账户拥有此仓库

  • … 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“营销与社交媒体”中的其他服务器比较i

  • 星标数多于此分类中其他 3567 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 3567 个服务器的 16% 更新
  • 基础检查结果等于或优于此分类中其他 3567 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

Periscope MCP 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(0.10.4)于4个月前进入注册中心。

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。

有什么可以替代它?

同一分类中有:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

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

MCP YouTube Transcript

作者:jkawamoto

An MCP server retrieving transcripts of YouTube videos

在你的电脑上运行★ 495MIT10天前更新
安装

Google Analytics MCP

作者:surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

在你的电脑上运行★ 244MIT10天前更新
安装

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

在云端运行★ 137MIT11天前更新
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。

periscope-mcp

An MCP server that gives AI agents 74 Playwright tools to QA, test, and analyze web apps — static sites, SPAs, and apps behind a login — returning hard verdicts, not screenshots to squint at. Not a thin wrapper around browser APIs; the tools are shaped around how agents actually work:

  • Hard results, not screenshot-squinting — assert_condition returns passed: true/false with the actual value; checks return structured issues.
  • One call instead of ten — auto_fill_form detects, infers, and fills a whole form; interact_and_test batches 25 action types with checks; test_project crawls and audits an entire site.
  • Real web-app testing — persistent authenticated sessions (form/basic/ cookie auth, plus a visible interactive login for 2FA/SSO/CAPTCHA that then runs headless), multi-step flows, network mocking, state snapshots, and real INP measured from the interactions it drives.
  • Honest responses — failures say what happened *and* what to do next (expired session vs. browser crash vs. eviction); silent no-ops like ignored drags come back flagged, not as fake success.
  • Debugging built in — captured API response bodies, console/network logs, network mocking, and state snapshots/diffs, no setup calls needed.
  • Audits agents can't get from a browser binding — accessibility, SEO, and GEO/agentic-search readiness (robots.txt AI-crawler access, llms.txt, WebMCP), plus real Lighthouse.

Playwright + headless Chrome underneath; site crawling, responsive testing, and screenshot diffing on top. Works with any MCP client — Claude Code, Codex, Cursor, Windsurf, Gemini CLI, custom agents, or anything else that speaks MCP over stdio.

Why not just playwright-mcp?

playwright-mcp is excellent at what it is: general browser control over MCP, with tools that mirror Playwright's own API. If the job is "browse this site, click around, extract something," use it.

Periscope exists for a different job: testing and auditing a site or web app, then reporting findings — and its tools encode the testing knowledge an agent would otherwise have to reinvent every session:

Raw browser controlPeriscope
Verifying an outcomeRead a screenshot or DOM dump and judgeassert_condition → hard passed: true/false + actual value
Filling a formOne call per field, agent invents test dataauto_fill_form — detects fields, infers realistic data, reports per-field failures
AuthRe-login by scripting clicks each sessionProjects persist form/basic/cookie auth; sessions share the logged-in context
Site-wide auditLoop pages manuallytest_project — crawl + accessibility/SEO/GEO/visual/functionality checks + saved report
Diagnosing a broken pageAsk for logs, replay requestsResponse bodies, console, and network are captured automatically; mock APIs with intercept_network
Silent failuresDrag "succeeds," nothing movedFlagged in the result, with the recovery path spelled out
AI-readiness audits—robots.txt AI-crawler access, llms.txt, WebMCP annotations, JSON-LD, plus real Lighthouse scores

The two aren't rivals — an agent can happily use playwright-mcp for browsing tasks and Periscope when it's wearing the QA hat. Periscope's design bets are simply about that hat: fewer, higher-level calls; structured verdicts instead of raw page state; and errors written to tell the agent what to do next.

Architecture

MCP client (AI agent)  -->  MCP Server (stdio)  -->  Playwright (Headless Chrome)

| | +-- Projects (JSON) +-- Persistent Sessions +-- Screenshots (PNG) +-- Network Interception +-- Reports (JSON) +-- Device Emulation +-- Videos (WebM)

How it works: your MCP client connects to this server over stdio. The server exposes 74 tools the agent can call to create projects, configure authentication, crawl websites, run static checks, and interactively test web applications using persistent browser sessions. Results (JSON + screenshots + videos) are returned to the agent for analysis.

Project Structure

periscope-mcp/

├── server.py # MCP server entry point (stdio wiring + dispatch) ├── tool_schemas.py # All 74 MCP tool definitions (schemas) ├── runtime.py # Shared singletons (project store, sessions, browser) ├── coercion.py # Argument coercion for MCP clients with stale schemas ├── handlers/ # Tool handlers, grouped by category │ ├── registry.py # @tool(name) decorator + HANDLERS registry │ ├── projects.py # create/list/get/delete project │ ├── auth.py # form login, basic auth, cookies, copy_auth │ ├── static_testing.py # test_url, crawl, test_project, reports, responsive │ ├── session_tools.py # open/close/list sessions, viewport, history │ ├── interactive.py # click, fill, steps, element queries, dialogs │ ├── analysis.py # forms, links, keyboard nav, tables, toasts, contrast │ ├── advanced.py # network mocking, storage, iframes, emulation, recording │ ├── agent_speed.py # assertions, smart find, auto-fill, snapshots │ ├── web.py # web_search, web_fetch │ ├── discovery.py # describe_tools catalog │ └── system.py # periscope_system: status, self-update, agents_md ├── tester.py # Playwright browser control + test orchestration ├── crawler.py # Page discovery (BFS crawl, same-domain only) ├── projects.py # Project CRUD + auth config storage ├── auth.py # Authentication handlers (form, basic, cookies) ├── sessions.py # SessionManager + PageSession — persistent page lifecycle ├── interactions.py # Interaction primitives (click, fill, execute_steps) ├── utils.py # Screenshot comparison (Pillow pixel diff) ├── config.py # Global settings (timeouts, paths, session limits) ├── checks/ │ ├── visual.py # Broken images, favicon, overflow, small text │ ├── accessibility.py # Alt text, labels, headings, lang, ARIA, keyboard nav │ ├── functionality.py # Broken links, forms, SEO, performance, link checker │ └── geo.py # GEO/agentic search: robots.txt AI crawlers, llms.txt, WebMCP, JSON-LD ├── tests/ # Unit tests (no browser) + tests/e2e/ (real browser + fixture pages) ├── data/ # Created at runtime (gitignored — contains credentials) ├── Dockerfile ├── docker-compose.yml └── .mcp.json.example # MCP registration template (copy to .mcp.json)

Prerequisites

  • Python 3.11+
  • Playwright + Chromium browser

Installation (Local)

Quick install (Debian/Ubuntu)

One command — clone and install:

git clone https://github.com/segentic-lab/periscope-mcp.git && cd periscope-mcp && ./install.sh

Fully unattended (no confirmation prompts):

git clone https://github.com/segentic-lab/periscope-mcp.git && cd periscope-mcp && ./install.sh -y

Already cloned? Just run ./install.sh from the repo directory.

The script installs apt prerequisites, creates the venv, installs Python dependencies and Playwright's Chromium, runs a headless self-test, and generates mcp-config.json with the correct absolute paths for this install (copy or merge it into your project's .mcp.json). Useful flags:

  • ./install.sh --system-chromium — use an existing Chromium/Chrome (sets CHROMIUM_PATH) instead of downloading Playwright's build
  • ./install.sh --skip-deps — never touch apt / use sudo
  • ./install.sh -y — non-interactive (no confirmation prompts)

On any other platform the script doesn't modify your system — it prints the exact commands to run for your OS (./install.sh --manual macos|fedora|arch|suse|windows to pick explicitly).

Updating
./update.sh

Pulls the latest source from GitHub (git pull --ff-only) and refreshes the install: Python dependencies, Playwright browser (kept on system Chromium if that's what the install uses), the registry + headless-launch self-test, and a regenerated mcp-config.json. Works on any platform with an existing install. Your data/ directory (projects, credentials, screenshots, reports) is never touched.

  • ./update.sh --force — stash local modifications to tracked files first (recover with git stash pop)
  • ./update.sh --full — also re-check apt prerequisites on Debian/Ubuntu (uses sudo)

If you have local modifications, the script refuses and lists them instead of overwriting.

Manual install
# Clone the repo

cd periscope-mcp

Create virtual environment

python3 -m venv venv source venv/bin/activate

Install dependencies

pip install -r requirements.txt

Install Chromium for Playwright

playwright install chromium

Installation (Docker)

docker compose up -d

See Docker Deployment section below.

Connecting an MCP Client

Periscope is a standard stdio MCP server: point any MCP client at venv/bin/python server.py and you're done. ./install.sh generates mcp-config.json with the correct absolute paths for your machine; most clients accept that shape directly:

{

"mcpServers": { "periscope": { "command": "/path/to/periscope-mcp/venv/bin/python", "args": ["/path/to/periscope-mcp/server.py"] } } }

Client-specific examples:

  • Claude Code — copy the config into the project as .mcp.json (cp .mcp.json.example .mcp.json and adjust paths), or run claude mcp add periscope -- /path/to/venv/bin/python /path/to/server.py
  • Cursor / Windsurf — add the block above to ~/.cursor/mcp.json / ~/.codeium/windsurf/mcp_config.json
  • Codex CLI — add to ~/.codex/config.toml: [mcp_servers.periscope] with command and args as above
  • Custom agents — any MCP SDK client can spawn the server over stdio with the same command and args

After configuring, restart your client.

Teaching your agent to use the tools

Two options, depending on your agent:

  • Claude Code (recommended): install the skill. SKILL.md (repo root; also exposed at skills/periscope/ in the Claude Code skill layout) is a Claude Code skill — it auto-triggers on web-testing tasks and loads a distilled operating guide (workflow decision table + the pitfalls) only when needed, costing ~0 context otherwise:
  ln -s "$(pwd)/skills/periscope" ~/.claude/skills/periscope

A symlink keeps it current with ./update.sh (copy the folder instead if you prefer a frozen version).

  • Any other MCP client: paste the guide. AGENTS.md contains a ready-made system-prompt block — workflows, tool-selection guidance, and known pitfalls. Paste its contents into your agent's system prompt (or custom instructions).

Either way, the agent can always fetch the current full guide from the running server via periscope_system(action="agents_md") and the complete catalog via describe_tools().

MCP Tools Reference (74 tools)

Project Management (4 tools)
ToolDescriptionRequired Params
create_projectCreate a new testing projectname, base_url
list_projectsList all projects_(none)_
get_projectGet project detailsname
delete_projectDelete project + dataname
Authentication (7 tools)
ToolDescriptionRequired Params

| set_form_login | Configure

只显示了开头部分;其余内容请在仓库中阅读

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