autodemo

autodemo

MCP server that turns any running web app into demo videos, interactive walkthroughs, and marketing captures via one command. Enables AI agents to show their work with regenerated demos on every PR.

Category
访问服务器

README

<div align="center">

AutoDemo

Demos as code. Turn any running web app into demo videos, interactive walkthroughs, and marketing captures — in one command. Regenerated by CI, so they can never go stale.

CI npm License: MIT MCP

Product page · Quick start · GitHub Action · For AI agents · Recipes · Contributing

</div>


autodemo demo "Sign up and open the dashboard" --url http://localhost:3000

That single command drives a real browser through your real app and produces:

Artifact What it's for
video.mp4 launch posts, landing pages, PR descriptions — cursor, click rings, human-paced typing
index.html static, embeddable interactive walkthrough (step screenshots + notes, keyboard navigable)
assets/*.png named marketing captures of real UI regions, for homepages and decks
run.json reproducible metadata — timings, steps, artifact contract for tooling

The teaser below was generated by AutoDemo, about its own product page, in CI:

AutoDemo teaser

Why

Demos and screenshots rot the moment the UI changes. Re-recording them is manual, slow, and always last on the list. Interactive-demo SaaS tools fix freshness with $300–500/month plans, per-seat pricing, and a browser extension that captures snapshots into their cloud.

AutoDemo treats demos like the rest of your software:

  • Versioned — scenarios are YAML in your repo, reviewed like code
  • Reproducible — deterministic Playwright steps, or AI steps when you want speed
  • Continuous — a 5-line GitHub Action regenerates everything on merge; a failing demo is a failing user flow
  • Yours — runs on your machine and your CI; no cloud, no telemetry, MIT licensed

Quick start

One-line install (macOS / Linux / WSL — installs Bun, the CLI, and a browser):

curl -fsSL https://raw.githubusercontent.com/praveen-palanisamy/autodemo/main/install.sh | bash

Or zero-install / per-project:

bunx @praveen-palanisamy/autodemo --help          # Bun
npm add -D @praveen-palanisamy/autodemo           # or as a dev dependency
bunx playwright install chromium

1. The magic moment (AI-authored)

With any LLM key in your env (ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, GROQ_API_KEY — or a local OLLAMA_HOST, auto-detected):

autodemo demo "Sign up, create a project, open the dashboard" --url http://localhost:3000

Watch the browser do it, then open the printed video.mp4 and walkthrough. Add --save to keep the scenario for replay.

2. Deterministic demos (no LLM needed)

autodemo init   # writes a commented .autodemo.yml
scenarios:
  signup:
    description: "Signup with readable typing and click highlights"
    steps:
      - type: goto
        url: /signup
      - type: fill
        selector: "[data-testid=email]"
        value: "maya@example.com"
        typing: true
      - type: click
        selector: "[data-testid=submit]"
      - type: waitFor
        text: "Dashboard"
      - type: screenshot
        name: dashboard-hero
        selector: "[data-testid=dashboard]"
autodemo run signup --url http://localhost:3000          # one scenario
autodemo run --all --url http://localhost:3000 --headless # all of them (CI)

3. Keep them fresh forever (CI)

- uses: praveen-palanisamy/autodemo@v0
  with:
    url: http://localhost:3000

Full inputs and recipes: docs/GITHUB_ACTION.md.

For AI agents

AutoDemo is agent-native: coding agents use it to show their work — a demo video on every PR.

bunx @praveen-palanisamy/autodemo mcp --no-tui    # MCP server over stdio

One-line registration for Cursor / Claude Code / Codex, JSON CLI contracts, and a drop-in rules snippet: docs/AGENTS.md.

Features

  • Any LLM, or none — OpenAI, Anthropic, Google, Groq, Ollama/local, any OpenAI-compatible endpoint; deterministic scenarios need zero keys
  • Authenticated flows — reusable browser storage state; login once, demo logged-in forever
  • Marketing-grade output — dev overlays hidden, loading noise trimmed (videoStartStep), named region captures, custom cursor & click highlights
  • Story tools — on-screen narrate beats, per-step notes in walkthroughs
  • Interactive TUI — wizards for recording and running (autodemo record --interactive)
  • CI-grade--json output, stable exit codes, trace.zip on failure, artifacts contract in run.json

How it compares

AutoDemo Demo SaaS (Supademo, Arcade, Storylane…) Screen recorders
Price Free, OSS $300–500/mo for HTML capture, per-seat $10–30/mo
Freshness Regenerated in CI Manual re-capture Manual re-record
Output Video + walkthrough + stills, one run Usually one format Video only
In git / code review
Agent-operable (MCP)

The SaaS tools are great for no-code editing, analytics, and hosted demo hubs. AutoDemo is for teams who want demos to be build artifacts.

Docs

CLI reference commands, flags, exit codes
Configuration .autodemo.yml, step types, LLM providers, auth state
GitHub Action demos in CI
AI agents MCP setup, JSON CLI, rules snippet
Recipes copy-paste scenarios
Architecture engines, runner, artifact pipeline
Testing · Local CI development workflows

Requirements

  • Bun ≥ 1.3 (the installer sets it up)
  • Playwright Chromium (one-time bunx playwright install chromium)
  • ffmpeg for MP4 export (optional — everything else works without it)

Contributing

The 15-minute setup, project tour, and good first issue list live in CONTRIBUTING.md. The lowest-friction contribution is a scenario recipe.

bun install && bun run playwright:install
bun test && bun run lint && bun run typecheck

License

MIT © Praveen Palanisamy and AutoDemo contributors.


<div align="center"> <sub>This README's teaser, the <a href="https://praveen-palanisamy.github.io/autodemo/">product page</a>, and its demo videos are all generated by AutoDemo itself — on every deploy.</sub> </div>

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选