KKM

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What is KKM

KKM is a portable fork of Kimi Code CLI with curated upstream fixes, multi-skill prompts, and native releases under the kkm command. It can read and edit code, run shell commands, search files, fetch web pages, and use Kimi or other compatible model providers.

Install

Download the archive for your platform from the latest GitHub Release. Each archive contains a single kkm executable and is accompanied by a SHA-256 checksum.

• Linux x64:

unzip kkm-linux-x64.zip
chmod +x kkm
sudo install kkm /usr/local/bin/kkm

• Windows x64 (PowerShell):

Expand-Archive .\kkm-win32-x64.zip -DestinationPath .\kkm
.\kkm\kkm.exe --version

On Windows, install Git for Windows before first launch because KKM uses its Git Bash environment. If Git Bash is installed in a custom location, set KIMI_SHELL_PATH to the absolute path of bash.exe.

Then run:

kkm --version

The npm package retains kimi as a compatibility alias, while KKM releases use kkm.

Quick Start

Open a project and start the interactive UI:

cd your-project
kkm

On first launch, run /login inside KKM and choose either Kimi Code OAuth or a Moonshot AI Open Platform API key. After login, try your first task:

Take a look at this project and explain its main directories.

Key Features

• Single-binary distribution. Install with one command: no Node.js setup, PATH gymnastics, or global module conflicts.
• Blazing-fast startup. The TUI is ready in milliseconds, so starting a session never feels heavy.
• Purpose-built TUI. A carefully tuned interface, optimized end to end for long, focused agent sessions.
• Video input. Drop a screen recording or demo clip into the chat and let the agent watch what is hard to describe in words — turn a reference clip into a LUT, a long video into a short, a screen recording into working code, and more.
• AI-native MCP configuration. Add, edit, and authenticate Model Context Protocol servers conversationally with /mcp-config, without hand-editing JSON.
• Rich plugin ecosystem. Install skills, MCP servers, and data sources from the marketplace or any GitHub repo, with each install's trust level surfaced up front.
• Subagents for focused, parallel work. Dispatch built-in coder, explore, and plan subagents in isolated contexts while keeping the main conversation clean.
• Lifecycle hooks. Run local commands at key points to gate risky tool calls, audit decisions, trigger desktop notifications, or connect to your own automation.
• Editor & IDE integration (ACP). Drive a KKM session straight from Zed, JetBrains, or any Agent Client Protocol client with kkm acp.

Use it in your editor (ACP)

KKM speaks the Agent Client Protocol, so ACP-compatible editors and IDEs (Zed, JetBrains, …) can drive a session over stdio. Log in once, then point your editor at the kkm acp subcommand — no extra login needed.

For Zed, add this to ~/.config/zed/settings.json:

{
  "agent_servers": {
    "KKM": {
      "type": "custom",
      "command": "kkm",
      "args": ["acp"],
      "env": {}
    }
  }
}

Then open a new conversation in Zed's Agent panel. See the upstream Using in IDEs guide for JetBrains setup and troubleshooting.

Docs

• Getting Started
• Interaction and approvals
• Sessions
• Using in IDEs (ACP)
• Configuration
• Command reference

Develop

Requirements: Node.js ≥ 24.15.0, pnpm 10.33.0.

git clone https://github.com/Pidbid/kkm.git
cd kkm
pnpm install

pnpm dev:cli    # run the CLI in dev mode
pnpm test       # run tests
pnpm typecheck  # TypeScript check
pnpm lint       # oxlint
pnpm build      # build all packages

See CONTRIBUTING.md for the full contribution guide.

Community

• Issues
• For security vulnerabilities, see SECURITY.md.

Acknowledgements

KKM is forked from MoonshotAI/kimi-code. Its TUI is built on pi-tui.

License

Released under the MIT License.