Browser

Lightpanda Browser

The headless browser built from scratch for AI agents and automation.
Not a Chromium fork. Not a WebKit patch. A new browser, written in Zig.
16x lighter and 9x faster than Chromium.

Benchmarks

Requesting 933 real web pages over the network on a AWS EC2 m5.large instance. See benchmark details.

Quick start

Install

Package Managers

Latest nightly from Homebrew:

brew install lightpanda-io/browser/lightpanda

Latest nightly from Arch Linux User Repository:

yay -S lightpanda-nightly-bin

Download from the nightly builds

You can download the last binary from the nightly builds for Linux and MacOS for both x86_64 and aarch64.

For Linux

curl -L -o lightpanda https://github.com/lightpanda-io/browser/releases/download/nightly/lightpanda-x86_64-linux && \
chmod a+x ./lightpanda

Verify the binary before running anything:

./lightpanda version

Linux aarch64 is also available

Note: The Linux release binaries are linked against glibc. On musl-based Linux distributions (Alpine, etc.) the binary fails with cannot execute: required file not found because the glibc dynamic linker is missing. Use a glibc-based base image (e.g., FROM debian:bookworm-slim or FROM ubuntu:24.04) or build from sources.

Android / Termux: there is no native Android build. The Linux aarch64 binary needs the glibc loader (/lib/ld-linux-aarch64.so.1), which Android's Bionic libc does not provide, so it fails with the same cannot execute: required file not found error.

For MacOS

curl -L -o lightpanda https://github.com/lightpanda-io/browser/releases/download/nightly/lightpanda-aarch64-macos && \
chmod a+x ./lightpanda

MacOS x86_64 is also available

For Windows + WSL2

Lightpanda has no native Windows binary. Install it inside WSL following the Linux steps above.

WSL not installed? Run wsl --install from an administrator shell, restart, then open wsl. See Microsoft's WSL install guide for details.

Your automation client (Puppeteer, Playwright, etc.) can run either inside WSL or on the Windows host. WSL forwards localhost:9222 automatically.

Install from Docker

Lightpanda provides official Docker images for both Linux amd64 and arm64 architectures. The following command fetches the Docker image and starts a new container exposing Lightpanda's CDP server on port 9222.

docker run -d --name lightpanda -p 127.0.0.1:9222:9222 lightpanda/browser:latest

Dump a URL

./lightpanda fetch --obey-robots --dump html --log-format pretty  --log-level info https://demo-browser.lightpanda.io/campfire-commerce/

You can use --dump markdown to convert directly into markdown, or --dump png > page.png or --dump pdf > page.pdf for a text-only rendering of the page. --dump structured_data prints the page's JSON-LD, OpenGraph, Twitter card, meta and link tags as JSON, like the MCP structuredData tool. --wait-until, --wait-ms, --wait-selector and --wait-script are available to adjust waiting time before dump.

Start a CDP server

./lightpanda serve --obey-robots --log-format pretty  --log-level info --host 127.0.0.1 --port 9222

Once the CDP server started, you can run a Puppeteer script by configuring the browserWSEndpoint.

import puppeteer from 'puppeteer-core';

// use browserWSEndpoint to pass the Lightpanda's CDP server address.
const browser = await puppeteer.connect({
  browserWSEndpoint: "ws://127.0.0.1:9222",
});

// The rest of your script remains the same.
const context = await browser.createBrowserContext();
const frame = await context.newPage();

// Dump all the links from the frame.
await frame.goto('https://demo-browser.lightpanda.io/amiibo/', {waitUntil: "networkidle0"});

const links = await frame.evaluate(() => {
  return Array.from(document.querySelectorAll('a')).map(row => {
    return row.getAttribute('href');
  });
});

console.log(links);

await frame.close();
await context.close();
await browser.disconnect();

Start a webdriver Bidi server

Use --protocol webdriver to enable Bidi support. You can start both, CDP and Bidi, with --protocol webdriver --protocol cdp

./lightpanda serve --obey-robots --log-format pretty  --log-level info --host 127.0.0.1 --port 9222 --protocol webdriver

Agent mode

lightpanda agent lets you drive the browser with a native agent. Describe what you want in plain English or with slash commands, and it controls the browser: navigating pages, clicking through flows, filling forms, extracting structured data. Think of it as a robot you're directing to use the web, more than a chatbot you're having a conversation with.

Because the agent runs inside the same process as the browser, every tool call is a direct operation and you retain Lightpanda's speed and memory advantage.

The output of an agent session is a PandaScript: vanilla JavaScript with a small set of native browser primitives built directly into Lightpanda. Run /save to export one from your current session, then replay it with lightpanda run <script>.js. Scripts are deterministic and token-free, so you can prototype with the LLM and ship the output to production without a model at runtime.

It supports Anthropic, OpenAI, Gemini, Google Vertex AI, Mistral, Hugging Face, the multi-lab gateways Vercel AI Gateway and OpenRouter (one key for hundreds of models), any OpenAI-compatible endpoint via OPENAI_BASE_URL, and local models via Ollama or llama.cpp. You can also run without an LLM using --no-llm, which drops you into the REPL. See the agent documentation for the full reference.

./lightpanda agent                                    # auto-detects API key from env
./lightpanda agent --task "top story on news.ycombinator.com?"
./lightpanda agent --no-llm                           # basic REPL, no LLM
./lightpanda run session.js                           # run a recorded script
cat session.js | ./lightpanda run -                   # ...or pipe one in via stdin
./lightpanda agent --provider gemini --task "..."     # force a specific provider
./lightpanda agent --list-models                      # models available for the detected provider
VERTEX_API_KEY=... ./lightpanda agent --provider vertex             # Vertex AI, express mode
GOOGLE_CLOUD_PROJECT=my-proj ./lightpanda agent --provider vertex   # Vertex AI, token via gcloud auth
AI_GATEWAY_API_KEY=... ./lightpanda agent --provider vercel --model moonshotai/kimi-k2   # any model behind Vercel AI Gateway
OPENROUTER_API_KEY=... ./lightpanda agent --provider openrouter --model anthropic/claude-sonnet-5   # any model behind OpenRouter
OPENAI_BASE_URL=https://my-gateway/v1 OPENAI_API_KEY=... ./lightpanda agent            # any OpenAI-compatible server

Native MCP and skill

The MCP server communicates via MCP JSON-RPC 2.0 over stdio.

Add to your MCP configuration:

{
  "mcpServers": {
    "lightpanda": {
      "command": "/path/to/lightpanda",
      "args": ["mcp"]
    }
  }
}

HTTP transport and independent sessions

For serving several agents from one process, start the MCP server over HTTP instead of stdio by giving it a port (add --host x.x.x.x to specify the interface to listen on):

lightpanda mcp --port 9223

Clients POST JSON-RPC to http://host:9223/mcp. Each connection is routed to its own browsing session — its own page, cookies and memory — so agents no longer clobber each other's page:

• A client that initializes without an Mcp-Session-Id header is assigned a fresh session; the id comes back in the response's Mcp-Session-Id header. Send it on subsequent requests to stay on that session (isolation).
• Two agents that send the same Mcp-Session-Id share one browsing context (sharing — e.g. a workflow where several agents work the same page).
• The session_new, session_list and session_close tools manage sessions explicitly. Sending DELETE /mcp with an Mcp-Session-Id closes that session.