
AIR SDK
io.github.ArcedeDev由 GitHub 账号 ArcedeDev 发布v0.2.12更新于 Oct 24, 2026
Collective intelligence for browser automation agents. Site capabilities, selectors, and extraction.
概览
为浏览器自动化代理提供预先验证的站点能力、CSS 选择器和结构化提取,使其无需猜测 DOM 即可操作。
- 可以做什么
- AIR SDK 提供用于发现网站可自动化操作的工具,返回带 CSS 选择器和回退方案的执行计划,从 URL 提取结构化数据,并从本地或远程文件(如 PDF、DOCX、XLSX、CSV)提取文本。它还接受执行结果上报,以改进共享的站点情报。它以 stdio 本地 MCP 服务器方式运行,可包装现有的 Playwright、Puppeteer 或 Browser Use 页面。
- 适用场景
- 适用于构建或运行浏览器自动化代理、需要反复检查页面并判断点击哪些元素的场景,用选择器查询和能力发现替代 LLM 的 DOM 推理。它属于早期研究预览版,应视为实验性功能。
- 运行要求
- 需要 Node.js 18 或更高版本。需要来自服务商控制台的 AIR_API_KEY,通过环境变量提供或保存在本地凭据文件中。可选的对等依赖为 Playwright、Puppeteer 或 Browser Use。需要访问服务商 API 的网络连接。免费额度为每月 1,000 次执行。
安装
在 SourceWeft 中
- 打开 控制台中的 AIR SDK,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
AIR SDK
Collective intelligence for agents. Stop your agents from guessing how to use the web. Let them know what to do. Think; hive mind. Let's make the open agent internet.
[npm version] [downloads] [license] [docs] [tests] [typescript strict]
Install · Quick Start · Why · Agent Skill · Docs
Your browser agent wastes tokens and time every time it asks an LLM what to click. AIR SDK replaces guessing with knowing. This is an early research preview.
Up to 7,000x cost reduction and 280x faster vs frontier models. One function call. Zero code changes.
Benchmarks
Measured across 8 major domains, 40 cold API calls, cache disabled. LLM baseline priced at Frontier Model ($15/$75 per M tokens). AIR SDK at Scale tier ($149/mo, 250K executions).
The more complex the workflow, the more you save. LLM costs compound — every action adds to the conversation context, making each subsequent round trip more expensive. AIR's macro path is always one API call, regardless of how many steps the workflow has.
Methodology & raw data
LLM baseline: Agent inspects page DOM, reasons about which elements to interact with, generates tool calls. Frontier Model pricing ($15/M input, $75/M output).
- 1 action: ~4,000 input + 800 output tokens x 2 round trips = ~9,600 tokens, ~$0.24, ~4s reasoning time.
- 10 actions: Context grows with each action (conversation history accumulates). Average ~6,000 input + 1,000 output tokens x 2.5 round trips per action = 25 total LLM calls, ~175,000 tokens, ~$4.13, ~50s reasoning time.
- Sonnet 4 comparison: 5x cheaper per token — 1 action: ~$0.05, 10 actions: ~$0.83. Still 80–1,400x more expensive than AIR at Scale.
AIR SDK macro path: Pre-verified CSS selectors returned via API. Agent executes directly — no DOM inspection, no LLM reasoning. Cost = plan price / included executions.
Raw API latency (40 measurements, cache disabled):
- browse_capabilities: 180ms median, 148ms min, 421ms p95
- execute_capability: 178ms median, 146ms min, 333ms p95
- Combined: 354ms median, 304ms min, 1010ms p95
Cost per action by tier:
Capabilities discovered: 16 avg per domain (range: 3–39)
Last run: 2026-03-20 | Run benchmark yourself: npx tsx benchmark/run.ts
Prerequisites
- Node.js >= 18
- One of: Playwright, Puppeteer, or Browser Use (optional peer dependencies)
Install
Agent Skill (recommended for AI coding agents):
Free tier included. No credit card. Make the network smarter, star the repo and share it ⭐
Lightweight Alternatives
Don't need the full SDK? We publish standalone packages for common use cases:
Quick Start
Wrap your existing Playwright page. Nothing else changes.
Also works with Puppeteer and Browser Use:
Why
Browser automation is fragile. Selectors break. Sites change. Your agent has no idea what's possible until it's already on the page.
AIR SDK gives your agent three things:
How it works: Wrap your page with withAIR(). The SDK observes actions, resolves selectors, and preloads site capabilities. Your code doesn't change — it just works better.
Privacy-first: Input values, cookies, and PII are never sent. See our privacy docs →
Credential Management
API keys are stored at ~/.config/air/credentials.json with 0600 permissions (owner read/write only).
Key resolution order: AIR_API_KEY env var → ~/.config/air/credentials.json → .env in current directory.
Agent Skill
Give your coding agent site intelligence with one command:
This auto-detects Claude Desktop, Claude Code, Cursor, Windsurf, and OpenClaw, writes the MCP server config, and injects your API key. It installs @arcede/air-sdk globally for fast agent startup (~2s instead of ~60s with npx) and writes the absolute binary path to each config to avoid npx version caching issues. Restart your agent and it instantly has new tools.
Manual setup (Claude Desktop, Claude Code, Cursor, Windsurf, OpenClaw)
Requires global install:
npm install -g @arcede/air-sdk. If not installed globally, replace"command": "air-sdk"with"command": "npx"and"args": ["--mcp"]with"args": ["-y", "@arcede/air-sdk", "--mcp"].
Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json:
Claude Code:
Cursor — add to ~/.cursor/mcp.json:
Windsurf — add to ~/.codeium/windsurf/mcp_config.json:
OpenClaw — add to ~/.openclaw/openclaw.json:
Tools available:
OpenAI Skill
AIR SDK is also available as an OpenAI hosted shell skill for gpt-5.4 and gpt-5.4-mini:
Then use in the Responses API:
Requires api.agentinternetruntime.com in your org network allowlist.
Configuration
Machine Payments Protocol
AIR SDK supports x402 micropayments, enabling your agent to pay for premium site access without pre-registration:
Examples
See examples/agents/ for working agent examples:
- Research Agent — Multi-source research with capability-aware navigation
- Price Comparison — Cross-site price monitoring with resilient selectors
- Capability Scout — Discover and map capabilities across domains
- Site Monitor — Track site changes with resilient selectors
Contributing
See CONTRIBUTING.md. PRs welcome.
Links
License
来源:README.md,提交 e487230
工具
0版本历史
1- v0.2.12最新Sep 16, 2026
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