Screenpipe：本地屏幕录制工具助力AI智能体工作

Louis 推出了 Screenpipe，这是一款 YC S26 初创项目，旨在为 AI 智能体提供可搜索的工作记忆 1。该应用在本地录制屏幕和音频 1，通过监听操作系统事件、配对截图和系统可访问性树来构建本地 SQLite 数据库 1。

Screenpipe 采用 Rust、MLX 和 Onnx 等技术栈开发 1。其 AI PII 模型在本地运行，占用资源极少，仅需不到 1% 的 CPU 和少于 400 MB 的 RAM 1。该工具支持多种 AI 模型进行任务自动化、信息检索和个人知识库维护 1。

在许可方面，Screenpipe 对个人非商业、非营利、教育和研究使用免费，商业使用需要付费许可证 1。许可证改变前的版本仍可在 MIT 许可下获得 1。应用提供桌面版和 CLI 两种形式，支持 macOS、Windows 和实验性 Linux 支持 1。源代码可在 GitHub 获取 1。

Louis has launched Screenpipe, a Y Combinator S26 project designed to record screen and audio locally, creating a searchable work memory for AI agents 1. The application constructs a local SQLite database by monitoring operating system events and pairing screenshots with system accessibility trees, enabling AI models to automate tasks, retrieve information, and maintain personal knowledge bases 1.

The platform is built using Rust, MLX, and Onnx technologies 1. Its AI PII model runs locally while consuming less than 1% CPU and under 400 MB of RAM 1.

Screenpipe follows a freemium model: personal, non-commercial, non-profit, educational, and research uses are free, while commercial applications require a paid license 1. Versions released prior to license changes remain available under the MIT license 1. The source code is publicly accessible at https://github.com/screenpipe/screenpipe 1.

The application is available as both a desktop application and command-line interface, with support for macOS, Windows, and experimental Linux support 1.