HyperAgent is an open-source browser-automation framework (npm @hyperbrowser/agent) that layers natural-language task execution on top of Playwright, letting an LLM navigate pages, extract data, and complete web flows without hand-written selectors. Distinction (dedup-confirmed): this is a separate product from the existing hyperbrowser catalog tool — hyperbrowser is the vendor's paid, hosted cloud browser infrastructure (stealth/proxy/session infra), whereas HyperAgent is the free, self-hostable agent framework you run yourself with your own LLM key. HyperAgent can optionally target Hyperbrowser's cloud for scaled/stealth browsing, but does not require it and runs against a local Chromium out of the box. Two buyer notes: the license is AGPL-3.0 (strong network-copyleft — if you expose it as a hosted service, the source-sharing obligation applies, which matters for commercial SaaS use); and page/DOM content is sent to whichever LLM you configure, by design.
HyperAgent
Open-source natural-language browser automation framework for AI agents
An AGPL-3.0 TypeScript framework that drives a real browser from natural-language tasks — the self-hostable OSS framework from Hyperbrowser, distinct from the vendor's paid cloud browser product.
Pricing
Free and open source (AGPL-3.0). Self-hostable at no license cost; bring your own LLM API key. Optionally runs against Hyperbrowser's separate paid cloud browser infrastructure, but that is a distinct product and not required.
Platforms
TypeScript / Node library (npm `@hyperbrowser/agent`), built on Playwright, controlling Chromium via natural-language tasks. Runs locally / self-hosted; optional Hyperbrowser cloud backend. Maintained by S2 Labs Inc.
Categories
Tags
Alternatives
Browser Use
AI agent framework for web browser automation
Browser Use is an open-source AI agent framework with 99K+ GitHub stars enabling LLMs to control web browsers via natural language. Y Combinator-backed, it lets agents navigate sites, fill forms, extract data, and complete multi-step tasks autonomously. Built on Playwright with vision-based element detection, multi-tab management, cookie persistence, and self-correcting actions. Supports OpenAI, Anthropic, and local models with a simple Python API for building custom browser agents.
Stagehand
AI-powered web browser automation with Playwright
Stagehand is an open-source browser-agent SDK from Browserbase that combines deterministic browser automation with AI primitives such as act(), extract(), observe(), and agent(). Instead of relying only on brittle selectors, developers can use natural-language actions, Zod-backed structured extraction, page observation, action caching, and Browserbase cloud-browser infrastructure for production web automation.
Skyvern
Browser automation with AI vision — no XPath or DOM parsing needed
Skyvern automates browser-based workflows using LLMs and computer vision instead of brittle XPath or CSS selectors. It understands web pages visually, navigating forms, clicking buttons, and extracting data like a human would. Achieved 85.85% success rate on WebVoyager benchmark and SOTA on WRITE tasks for RPA. 21,000+ GitHub stars, AGPL-3.0 licensed. Skyvern Cloud offers managed usage-based hosting for teams that prefer not to self-host the infrastructure.
Steel
Open-source browser infrastructure for AI agents at scale
Steel is an open-source browser API purpose-built for AI agents, providing managed headless browser sessions with anti-bot bypass, proxy rotation, CAPTCHA solving, and session persistence. It handles the infrastructure layer that browser automation agents like Browser Use and Stagehand run on top of. Self-hostable or available as a cloud service. Over 6,000 GitHub stars.
Related Tools
KaibanJS
JavaScript framework for building and visualizing multi-agent workflows on a Kanban board
KaibanJS is an MIT-licensed JavaScript framework for defining AI agents, tasks, tools, and teams, then orchestrating their work through a Kanban-inspired runtime and visual board. It can run inside Node.js, React, or Next.js projects, supports custom UIs and headless workflows, and provides real-time task-state visibility for multi-agent applications.
Sakana Fugu
Multi-agent model API that orchestrates frontier models behind one OpenAI-compatible endpoint
Sakana Fugu is a hosted model-provider API that exposes a learned multi-agent system as one OpenAI-compatible model. It dynamically routes coding, code review, research, and reasoning tasks across a frontier-model pool, with Fugu for lower-latency work and Fugu Ultra for harder workloads where answer quality matters more than cost or speed.
OpenWiki
LangChain CLI for maintaining agent-friendly codebase documentation
OpenWiki is LangChain’s open-source CLI for generating and maintaining an agent-focused wiki inside a codebase. It can create an openwiki/ documentation folder, update it from repository changes, add guidance to AGENTS.md or CLAUDE.md, and run via an interactive CLI or daily GitHub Action so coding agents have durable context without stuffing every detail into prompts.
Accomplish Coworker
Open-source desktop AI coworker for browsing and code execution.
Accomplish Coworker is an MIT-licensed open-source AI coworker that runs on the desktop, combining computer-use style browsing with code execution so agents can research, implement, run, and debug workflows in one local environment.
Headroom
Context compression for LLM apps and coding agents
Headroom is an Apache-2.0 context compression layer for LLM apps and coding agents. It compresses tool output, logs, files, RAG chunks, and agent history through a local library, proxy, wrapper, or MCP server, with retrieval hooks for bringing originals back when needed. Treat its savings numbers as Headroom-reported benchmarks, not independent aicoolies measurements.
Codebase Memory MCP
Codebase knowledge graph MCP server for AI coding agents
Codebase Memory MCP is an MIT-licensed MCP server that turns a repository into a persistent code knowledge graph for AI coding agents. It gives Claude Code, Cursor, Codex-style agents, and other MCP clients structural queries for functions, classes, call chains, routes, and architecture, helping them explore large projects without repeatedly rereading files or relying only on broad search.