Browserless

Reliable end-to-end testing

Cross-browser E2E testing framework by Microsoft supporting Chromium, Firefox, and WebKit with one API. Features auto-waiting, tracing with timeline/screenshots/DOM snapshots, codegen for recording tests, and parallel execution. Component testing for React, Vue, Svelte. Built-in API testing, network mocking, and mobile emulation. Known for reliability and speed vs Selenium/Cypress. 70K+ GitHub stars, rapidly becoming the E2E standard.

Headless Chrome Node.js API

Node.js library by Google that provides a high-level API for controlling headless or full Chrome and Chromium browsers programmatically. Used extensively for web scraping, automated testing, PDF generation, screenshot capture, form submission, and performance monitoring. Supports page navigation, DOM manipulation, network interception, and cookie management. Works with Chrome DevTools Protocol directly. The most widely-used browser automation tool in the Node.js ecosystem with 89K+ GitHub stars.

Production-grade web scraping and browser automation library

Crawlee is an open-source web scraping and browser automation library for Node.js and Python that handles the hard parts of building reliable crawlers. It manages proxy rotation, request queuing, automatic retries, session management, and fingerprint spoofing out of the box. Supports Puppeteer, Playwright, Cheerio, and HTTP-based crawling with a unified API. Built by Apify, it includes persistent storage, autoscaling concurrency, and TypeScript-first design for production deployments.

In-page AI browser agent via a single script tag

Page Agent is Alibaba's open-source JavaScript library that embeds an AI GUI agent directly into any web page through a single script tag injection. Unlike headless browser tools that operate externally, Page Agent works inside the DOM using text-based manipulation for natural language QA testing, enterprise copilots, and making legacy web apps AI-native. It supports BYOLLM with any model provider and requires no backend changes.

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.

Test and debug MCP servers before they ship

Open-source platform for inspecting, debugging and regression-testing MCP servers, MCP Apps and ChatGPT apps, with OAuth and protocol conformance for local and CI workflows.

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.