6-Minute Tutorial: Run the Leaked Claude Code Locally (Beginner-Friendly)

A hands-on tutorial for setting up and running the leaked Claude Code locally
This article explains how to set up the leaked version of Claude Code locally. It first clarifies the layered architecture between the application layer and LLMs, explaining how Claude Code achieves a superior programming experience through its sophisticated Agentic Loop mechanism. It then covers the technical background of the code leak and its model-agnostic design, and finally provides guidance on the prerequisites needed for local deployment.
Introduction: Why Claude Code Deserves Your Attention
Claude Code is a benchmark product in the AI Coding space, renowned for its powerful code comprehension and generation capabilities. However, due to official restrictions, regular users have had difficulty accessing it directly. After the recent Claude Code source code leak, community developers built a locally runnable version based on the leaked code, enabling ordinary users to experience its core capabilities.
This article will walk you through how to quickly set up and run the leaked version of Claude Code locally. Even without any programming background, you can complete the entire process in just 6 minutes.
The Relationship Between the Application Layer and LLMs: Why Claude Code Delivers a Better Experience
Before we begin, let's understand a key concept: when we use AI daily, we're not communicating directly with the large language model — there's an application layer in between.
Common application layer products include:
- Trae IDE: An AI programming tool by ByteDance
- Open Cloud (Lobster): A recently popular AI application
- Doubao: An AI assistant commonly used by non-programmers
- Claude Code: A professional-grade AI Coding tool
The application layer calls upon the LLM's reasoning and text generation capabilities, then returns processed results. Each application has its own unique business logic, which determines the difference in user experience even when using the same underlying model.
The layered architecture between the application layer and the underlying LLM is the core design paradigm of current AI product engineering. Underlying LLMs (such as GPT-4, Claude 3, Gemini, etc.) are essentially "text prediction engines" — they receive input token sequences and output the most probable continuation. The application layer, on the other hand, is responsible for converting user intent into structured prompts, managing multi-turn conversation context, calling external tools (such as code executors, file systems, search engines), and post-processing and formatting the model's output.
Claude Code's core competitive advantage lies precisely in its application layer design: it has a built-in sophisticated "Agentic Loop" mechanism that can autonomously plan task steps, invoke Bash commands, read and write files, execute tests, and dynamically adjust strategies based on execution results. This "think-act-observe" loop architecture extends far beyond the capability boundaries of ordinary chat-based AI assistants. This is why, even when the underlying model is replaced, Claude Code's application layer logic still delivers a programming experience significantly superior to regular AI conversations.

The Claude Code Leak: Technical Background and Community Practices
Claude Code is a command-line AI programming tool released by Anthropic, initially offered in closed-source form to paying users. In early 2025, its core application layer code (primarily implemented in JavaScript/TypeScript) circulated in the community, sparking widespread attention.
The leaked code revealed several key technical details: it employs a "Tool Use/Function Calling" mechanism, encapsulating file read/write, command execution, code search, and other capabilities as structured tools for the model to invoke. Its prompt engineering is extremely refined, containing extensive system prompts optimized for programming scenarios. The entire architecture exhibits excellent model agnosticism — the underlying model can be replaced with any service that supports standard API formats. This is the technical foundation that allows the community to connect it with third-party models like MiniMax, DeepSeek, and others.
Preparation: Three Essential Items for Running Claude Code Locally
Before the actual installation, you'll need to prepare the following three things:
1. Download the Leaked Claude Code Package
Community contributors have organized the leaked code into a locally runnable version (repository named "Cloud Code
Related articles
TutorialsChatGPT Plus Subscription Guide: Are GPT-5.5, image-2, and Codex Worth the Upgrade?
A detailed look at ChatGPT Plus features — GPT-5.5, image-2, and Codex — with a Plus vs Pro comparison and a complete step-by-step subscription guide for users outside the US.
TutorialsHarness AI Engineering in Practice: Using Claude Code to Master Enterprise-Level E-Commerce Development
Deep dive into Harness AI Engineering: master enterprise e-commerce development with Claude Code using the Rules, Skills, Wiki, and Changes framework.
TutorialsCursor + Codex Dual-IDE Collaboration: A Practical Methodology for Open-Source Project Customization
A complete methodology for open-source project customization based on real-world experience, detailing the Cursor+Codex dual-IDE workflow, seven-stage process, MVP validation, and AI source code reading techniques.