Steel

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.

Secure cloud sandboxes for AI agents

E2B provides secure cloud sandboxes that let AI agents execute code, run terminal commands, and interact with filesystems in isolated environments. Each sandbox spins up in ~150ms with its own OS, giving agents a safe space to run untrusted code. Supports Python, JavaScript, and any language via custom Dockerfiles. Used by AI coding assistants, data analysis agents, and code interpreters. SDK available for Python and JavaScript with a simple API for programmatic sandbox control.

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.

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.

Local microVM sandboxes for AI agent code execution

Microsandbox provides hardware-level isolated sandboxes for AI agents to execute code safely on local machines. Using libkrun microVMs and a 320ms bare-metal Linux/KVM homepage benchmark, it offers stronger isolation than Docker containers while staying lightweight enough for dev workstations. OCI-compatible with Python and Node.js runtimes. Apache-2.0 licensed with 6.6K+ GitHub stars.

Mozilla-backed browser infrastructure for AI agents

Tabstack is Mozilla's browser infrastructure service for AI agents, providing clean markdown extraction, structured JSON data, and automated browser actions through a fast API. With two-tier fetch escalation that achieves sub-600ms latency for static pages, robots.txt compliance, and ephemeral data handling, it offers an ethical alternative to aggressive web scraping tools — complete with an MCP server for Claude and Cursor integration.

Open standard for portable skills across AI agents

Agent Skills is the open SKILL.md folder specification for packaging reusable instructions, scripts, references, and assets that compatible AI agents load through progressive disclosure. Originally developed by Anthropic and released as an open standard, it defines the portable format itself—not an example library, marketplace, or hosted agent product.

Heterogeneous CPU-GPU inference and SFT for large MoE models

Open-source framework for running and fine-tuning large Mixture-of-Experts models with heterogeneous CPU-GPU execution, optimized kernels, limited VRAM and SGLang or LLaMA-Factory integrations.

Official Kubernetes and Helm reference stack built on the vLLM inference engine

Official vLLM reference implementation for scaling the existing inference engine on Kubernetes with Helm, request routing, KV-cache offload, autoscaling and Prometheus/Grafana observability.

Distributed inference orchestration above vLLM, SGLang and TensorRT-LLM

Open-source, datacenter-scale orchestration layer that coordinates vLLM, SGLang and TensorRT-LLM across nodes with disaggregated serving, KV-aware routing, multi-tier cache management and automatic scaling.

Open-source GPU control plane for scalable AI model serving

Open-source GPU cluster manager that configures vLLM, SGLang, TensorRT-LLM or custom engines, serves models through compatible APIs, and provisions SSH-accessible GPU instances across on-premises, Kubernetes and cloud environments.

Disaggregated KV cache storage and transfer for LLM serving

Open-source infrastructure for disaggregated LLM serving that pools KV caches across prefill and decode workers, with high-performance transfer, distributed storage and integrations for vLLM and SGLang.