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soongenwong/claudecode has 1,220 GitHub stars and 418 forks. GitHot measured 0 stars in 24 hours. Last checked 2026-11-09 07:39 UTC. Last push 2026-06-21.

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Open Source ClaudeCode Leaked. Same functionalities as Claude Code by Anthropic. Written in Rust, Ready to use immediately for free.

What you can do

  • Rust-powered: Built with Rust for memory safety, minimal binary size, and high execution speed.
  • Live TUI dashboard: A split-pane ratatui interface showing the agent's pipeline, a workspace tree that recolors as files are scanned/read/modified, and a syntax-highlighted diff that streams in character-by-character.
  • Agentic CLI: Interactive shell and one-shot prompt support for seamless terminal workflows.
  • Model flexible: Supports Anthropic-compatible and OpenAI-compatible providers, plus xAI/Grok aliases.

Measured star growth

in 24h
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in 7 days
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Net star changes over overlapping periods, not daily totals. Missing measurements are left blank. Stars measure attention, not software quality.

README.md

Original

ClaudeCode (Open Source)

A high-performance, open-source AI coding agent written in Rust.

ClaudeCode is a terminal-native CLI agent designed to bring advanced LLM capabilities directly into your development workflow. Built for speed, safety, and efficiency, it provides an interactive agent shell, workspace-aware tools, and persistent session management. It is an independent open-source implementation inspired by Claude Code, not the official Anthropic product.

Star History

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Key Features

  • Rust-powered: Built with Rust for memory safety, minimal binary size, and high execution speed.
  • Live TUI dashboard: A split-pane ratatui interface showing the agent's pipeline, a workspace tree that recolors as files are scanned/read/modified, and a syntax-highlighted diff that streams in character-by-character.
  • Agentic CLI: Interactive shell and one-shot prompt support for seamless terminal workflows.
  • Model flexible: Supports Anthropic-compatible and OpenAI-compatible providers, plus xAI/Grok aliases.
  • Workspace aware: Context-aware tools designed to understand your local codebase.
  • Session persistence: Resumeable sessions via JSON state management.
  • Extensible: Plugin-ready architecture for custom tools and skills.

Getting Started

Prerequisites

  1. Install Rust stable and Cargo.
  2. Set up your preferred API credentials.

Installation

From the repository root:

cd rust
cargo build --release -p claw-cli

# Install locally to your PATH for global access
cargo install --path crates/claw-cli --locked

Usage

Start the interactive shell:

claw

Run a single prompt:

claw prompt "summarize this workspace"

Resume a previous session:

claw --resume session.json /status

Launch the live split-pane dashboard (currently runs a scripted demo session):

claw dashboard   # alias: claw tui

The dashboard renders three panels — Agent Pipeline (left, a live step log), Workspace + System State (right, a file tree that recolors as files are scanned/read/modified, plus a progress gauge), and Live Diff (bottom, a syntax-highlighted diff that types in line-by-line). Press q, Esc, or Ctrl-C to exit. The UI is driven entirely by an AgentEvent stream, so it can be wired to the real agent loop without touching the rendering code.

Run claw --help for the full command list, including agents, skills, and system-prompt flows.

Authentication

Configure your environment variables based on your preferred provider:

Anthropic

export ANTHROPIC_API_KEY="..."
export ANTHROPIC_BASE_URL="https://api.anthropic.com"

OpenAI-compatible

export OPENAI_API_KEY="..."
export OPENAI_BASE_URL="https://api.openai.com/v1"

Grok / xAI

export XAI_API_KEY="..."
export XAI_BASE_URL="https://api.x.ai"

You can also authenticate via the CLI:

claw login

Frequently Asked Questions

What is this project? This is an independent, open-source implementation of a terminal-based coding agent, architecturally inspired by Claude Code.

Why Rust? Rust provides the performance, concurrency, and memory safety required for a tool that interacts deeply with local file systems and high-latency LLM APIs.

Can I use local models? Yes, if your local inference server exposes an OpenAI-compatible API and you point the relevant base URL and API key at it.

Is this the official Anthropic Claude Code? No, this is a community-driven open-source project.

Development

We welcome contributions. Please refer to CLAW.md for workspace-specific workflow guidance.

cd rust
cargo fmt
cargo clippy --workspace --all-targets -- -D warnings
cargo test --workspace

Repository Structure

  • rust/: Core CLI and runtime implementation.
  • src/: Python support code and utilities.
  • tests/: Verification suites for agentic behaviors.
  • CLAW.md: Internal workflow documentation.

Notes

  • This project is an open-source implementation.
  • It is not affiliated with or endorsed by Anthropic.

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