Moonshot AI Releases Kimi Code CLI: A Terminal AI Coding Agent Built in TypeScript for Next-Gen Agents - MarkTechPost

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Moonshot AI Releases Kimi Code CLI: A Terminal AI Coding Agent Built in TypeScript for Next-Gen Agents

June 6, 2026

Moonshot AI has released Kimi Code CLI, an open-source coding agent that runs in the terminal. The tool reads and edits code, runs shell commands, searches files, and fetches web pages. It then chooses its next step based on the feedback it receives. The project is MIT-licensed and lives on GitHub..

Kimi Code CLI is the successor to the older kimi-cli. The new agent is written in TypeScript and distributed via npm. It works out of the box with Moonshot AI’s Kimi models. It can also be configured to use other compatible providers.

What is Kimi Code CLI

Kimi Code CLI is an AI agent for software development and terminal operations. It can implement new features, fix bugs, and complete refactors. It can also explore an unfamiliar codebase and answer architecture questions. Batch file processing, builds, and chained test runs are supported too.

The execution model is feedback-driven. The agent plans steps, modifies code, runs tests, and reports its actions. Read-only operations run automatically by default. For file edits or shell commands, the agent asks for confirmation first. This approval flow keeps risky actions under developer control.

The CLI itself is free and MIT-licensed. Model access requires Kimi Code OAuth or a Moonshot AI Open Platform API key.

Key Features

Moonshot lists several features aimed at long, focused agent sessions:

Single-binary distribution. One command installs it, with no Node.js setup required.
Fast startup. Moonshot says the TUI is ready in milliseconds.
Purpose-built TUI. The interface is tuned for extended agent sessions.
Video input. Drop a screen recording or demo clip into the chat.
AI-native MCP configuration. Add and authenticate Model Context Protocol servers via /mcp-config.
Subagents for parallel work. Dispatch built-in coder, explore, and plan subagents in isolated contexts.
Lifecycle hooks. Run local commands to gate tool calls, audit decisions, or trigger notifications.

Installation and First Run

Two installation paths exist. The official script needs no pre-installed Node.js.

On macOS or Linux, run the install script:

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

On Windows, use PowerShell:

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irm https://code.kimi.com/kimi-code/install.ps1 | iex

The global npm install requires Node.js 24.15.0 or later:

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npm install -g @moonshot-ai/kimi-code

Verify the binary, then open a project and start the interactive UI:

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kimi --version
cd your-project
kimi

On first launch, type /login inside the UI. You can choose Kimi Code OAuth or a Moonshot AI Open Platform API key. To run one instruction without the UI, use kimi -p "your task". To resume the previous session, add -C.

Use Cases

Understanding a project: Ask for an architecture overview and a module dependency diagram.
Implementing a feature: Describe the signature, options, and acceptance criteria up front.
Fixing a bug: Give the symptom, reproduction steps, and expected behavior together.
Writing tests and refactoring: Extract repeated patterns, then run tests to confirm behavior.
One-off automation: Analyze logs and output call counts with p50 and p99 latencies.
Scheduled tasks: Ask the agent to set reminders or recurring checks via cron.

Plan mode is available through Shift-Tab or kimi --plan. It outputs a research plan before touching files. For safe batch work, --yolo or /yolo skips approval prompts. The /fork command creates an experimental branch you can abandon. The /compact command compresses context to free up tokens. For large investigations, the main agent can dispatch subagents in parallel.

How Kimi Code CLI Compares

Kimi Code CLI joins several established terminal coding agents. The table below compares it with three of them. Competitor details reflect mid-2026 and can change quickly.

Attribute	Kimi Code CLI	Claude Code	OpenAI Codex CLI	Gemini CLI
Developer	Moonshot AI	Anthropic	OpenAI	Google
Backing model	Kimi models	Claude models	GPT-5.3-Codex	Gemini 2.5 Pro
Language / runtime	TypeScript	Node.js	Rust	TypeScript
Install	Script or npm (Node.js ≥ 24.15.0)	Native installer or npm	npm / native	npm single binary
MCP support	Yes (`/mcp-config`)	Yes	Yes	Yes
Subagents	Yes (`coder`, `explore`, `plan`)	Yes	Yes	No (sequential)
Plan mode	Yes (`Shift-Tab`)	Yes	Yes	Yes
IDE integration	ACP (Zed, JetBrains)	VS Code, JetBrains	VS Code, IDEs	VS Code (Code Assist)
License	MIT	Proprietary	Open source	Apache 2.0

All four agents support the Model Context Protocol. They differ on backing model, language, license, and orchestration. Kimi Code CLI and Codex CLI both ship native subagents. Gemini CLI runs tasks sequentially without subagent support.

Key Takeaways

Kimi Code CLI is an MIT-licensed terminal coding agent from Moonshot AI.
It is written in TypeScript and installs via script or npm.
Built-in coder, explore, and plan subagents run in isolated contexts.
MCP servers are configured conversationally through /mcp-config, not raw JSON.
It succeeds kimi-cli and migrates existing configuration and sessions.

Marktechpost’s Visual Explainer

Kimi Code CLI · Guide 01 / 09

Overview

Kimi Code CLI

Moonshot AI’s open-source terminal coding agent that reads code, runs commands, and plans its next step.

Runs in your terminal as an AI coding agent
MIT-licensed · written in TypeScript · distributed via npm
Works with Kimi models or other compatible providers

Slide 02

What Is Kimi Code CLI?

Reads and edits code, runs shell commands, searches files
Fetches web pages and chooses the next step from feedback
Read-only actions run automatically by default
File edits and shell commands ask for confirmation first

Slide 03

Key Features

Single-binary distribution — no Node.js setup required
Built-in coder, explore, and plan subagents
AI-native MCP configuration via /mcp-config
Lifecycle hooks and video input support

Slide 04

Install

macOS / Linux

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

Windows (PowerShell)

irm https://code.kimi.com/kimi-code/install.ps1 | iex

npm (Node.js 24.15.0+)

npm install -g @moonshot-ai/kimi-code

Slide 05

First Run

kimi --version
cd your-project
kimi

Type /login → Kimi Code OAuth or Moonshot API key
kimi -p "your task" runs one instruction without the UI
kimi -C resumes the previous session

Slide 06

Use Cases

Understand a project: architecture overview and dependency map
Implement features with clear signatures and acceptance criteria
Fix bugs from symptom, reproduction steps, and expected behavior
Write tests, refactor, and automate log analysis or batch edits

Slide 07

Modes & Commands

Plan mode: Shift-Tab or kimi --plan
--yolo or /yolo skips approvals for safe batch work
/fork creates an experimental branch you can abandon
/compact compresses context to free up tokens

Slide 08

How It Compares

Attribute	Kimi Code CLI	Claude Code	Codex CLI	Gemini CLI
Model	Kimi models	Claude models	GPT-5.3-Codex	Gemini 2.5 Pro
Language	TypeScript	Node.js	Rust	TypeScript
Subagents	Yes	Yes	Yes	No
License	MIT	Proprietary	Open source	Apache 2.0

Slide 09

Key Takeaways

MIT-licensed terminal coding agent from Moonshot AI
Written in TypeScript; installs via script or npm
coder, explore, plan subagents in isolated contexts
MCP configured conversationally, not raw JSON
Succeeds kimi-cli; migrates config and sessions

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Michal Sutter

+ posts

Michal Sutter is a data science professional with a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michal excels at transforming complex datasets into actionable insights.

Moonshot AI Releases Kimi Code CLI: A Terminal AI Coding Agent Built in TypeScript for Next-Gen Agents

What is Kimi Code CLI

Key Features

Installation and First Run

Use Cases

How Kimi Code CLI Compares

Key Takeaways

Marktechpost’s Visual Explainer

Kimi Code CLI

What Is Kimi Code CLI?

Key Features

Install

First Run

Use Cases

Modes & Commands

How It Compares

Key Takeaways

Michal Sutter

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