Kimi Code, Moonshot AI's open-source coding agent, just shipped a wave of updates that collectively reframe what a terminal-based coding agent can do. The headline features , drag-in video context, a plugin marketplace, ACP-based IDE bridging, and autonomous goal mode , land on top of an already significant foundation: a full rewrite of the CLI from Python to TypeScript, and the upgrade to the Kimi K2.6 model underneath.

From CLI tool to coding platform

The entire codebase was rewritten from Python to TypeScript and Node.js , not an incremental update, but a new foundation with a redesigned architecture, installation flow, and configuration format. The practical payoff is immediate: faster cold starts, a proper full TUI with a status bar and approval panel, and a one-line install that requires no Python environment at all.

curl -fsSL https://code.kimi.com/kimi-code/install.sh | bash

That single command is the entire setup. Install with the official script , no Node.js required. On first launch, /login opens a browser for OAuth; no manual API key wrangling needed.

Video as a first-class coding input

The most novel addition is video context. You can now drag a video file directly into the CLI and use it as reference material for a coding task. The supported workflows include:

• Screen-recording-to-code: paste a screen recording and ask Kimi to reproduce the UI or workflow in code
• Reference-to-LUT: use a color-graded video clip as a reference to generate a color lookup table
• Long-video-to-short: summarize or extract key segments from a long recording

This is possible because Kimi K2.6 is a 1-trillion-parameter, native multimodal MoE (Mixture-of-Experts) model with only 32B parameters activated per token. Multimodality is baked into the base model, not bolted on. Many open coding models still ask you to choose between the model that codes and the model that sees. Kimi K2.6 is a 1T-parameter MoE model with 32B active parameters, a 262K context window, and native image and video input.