
AIR SDK
io.github.ArcedeDev由 GitHub 帳號 ArcedeDev 發布v0.2.12更新於 Oct 24, 2026
Collective intelligence for browser automation agents. Site capabilities, selectors, and extraction.
概覽
為瀏覽器自動化代理提供事先驗證過的網站能力、CSS 選擇器與結構化擷取,讓代理不必猜測 DOM 就能操作。
- 可以做什麼
- AIR SDK 提供工具來探索網站上可自動化的動作,回傳含 CSS 選擇器與備援方案的執行計畫,從 URL 擷取結構化資料,並從本機或遠端檔案(如 PDF、DOCX、XLSX、CSV)擷取文字。它也接受執行結果回報,以改善共享的網站情報。它以 stdio 本機 MCP 伺服器方式執行,可包裝現有的 Playwright、Puppeteer 或 Browser Use 頁面。
- 適用情境
- 適合在建置或執行瀏覽器自動化代理、需要反覆檢查頁面並判斷要點擊哪些元素時使用,以選擇器查詢與能力探索取代 LLM 的 DOM 推理。它屬於早期研究預覽版,應視為實驗性功能。
- 執行需求
- 需要 Node.js 18 或更新版本。需要來自服務商儀表板的 AIR_API_KEY,透過環境變數提供或存放在本機憑證檔案中。選用的對等相依套件為 Playwright、Puppeteer 或 Browser Use。需要連線至服務商 API 的網路。免費方案包含每月 1,000 次執行。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 AIR SDK,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
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
來源:README.md,提交 e487230
工具
0版本歷史
1- v0.2.12最新Sep 16, 2026
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