BrowserWing Lets AI Agents Run Recorded Browser Workflows Without Burning Tokens
BrowserWing exposes browser actions as MCP commands and Claude Skills, letting agents automate the web without burning tokens on every click.
PRO- BrowserWing wraps browser automation as MCP commands and Claude Skills for direct agent invocation. Repo
- Ships 78 built-in scripts covering GitHub, Hacker News, Reddit, YouTube, Amazon, Bloomberg, and more.
- Single Go binary installs via
npm install -g browserwingand exposes port 8080. - Includes 26+ REST endpoints, a CLI with structured exit codes, and a visual recorder with export.
- Optional CloakBrowser integration for defeating Cloudflare Turnstile and FingerprintJS.
- MIT licensed, cross-platform, and supports OpenAI, Claude, and DeepSeek for semantic extraction.
Getting an LLM to drive a browser usually means feeding it screenshots, waiting on DOM dumps, and burning tokens while the model figures out where to click. BrowserWing takes a different route by wrapping browser automation into MCP commands and Claude Skills, so an agent can call a pre-recorded workflow directly instead of reasoning through every interaction step by step.
Written in Go with a React frontend, the project has crossed 1.3k stars on GitHub. It ships as a single binary that runs Chrome or Chromium locally and exposes a REST API, an MCP server, a CLI, and a web UI on top of the same automation engine.
Workflows, not pixels
Most "AI browses the web" demos are inefficient. Every navigation, click, and extraction round-trips through the LLM, which is slow and expensive. BrowserWing flips this by letting you record a workflow once (login, search, scroll, extract) and then hand the agent a callable command that returns structured JSON. The model plans at the workflow level rather than the pixel level.
Two agent-facing protocols work out of the box:
- MCP (Model Context Protocol): the Anthropic-backed standard for tool servers. BrowserWing runs as an HTTP MCP server that any compatible client can plug into.
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