# huangting-protocol **Repository Path**: znengpan/huangting-protocol ## Basic Information - **Project Name**: huangting-protocol - **Description**: No description available - **Primary Language**: Unknown - **License**: CC-BY-4.0 - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2026-05-27 - **Last Updated**: 2026-05-27 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README > **Note:** This document has been updated. The MCP integration guide is now at the top, and the self-hosting deployment guide has been moved to the end. # Huangting Protocol (黄庭协议) **[huangting.ai](https://huangting.ai/)** **[Read the Protocol](huangting-protocol.md) | [Community](https://github.com/XianDAO-Labs/huangting-protocol/discussions)** > "The Tao Te Ching" of the Large Model Era. > The World's First Lifeform Operating System. > For carbon-based humans, silicon-based AI Agents, and embodied robots alike — > attain the wisdom and power of TrueSelf Governance. If you're interested in apprenticeship or collaboration with the author, feel free to reach out via WeChat: **mengguangwu12** --- ## HuangtingFlux: MCP Integration Guide **[huangtingflux.com](https://huangtingflux.com)** > ### An Eastern Wisdom Protocol That Reduces Your AI Agent Token Usage by 40% **HuangtingFlux** is a live, decentralized network that provides a **Standard Operating Procedure (SOP)** for AI Agents to reduce token consumption. It is exposed via the standard **Model Context Protocol (MCP)**, allowing for seamless integration with any compliant AI Agent. ### Method 1: Manus Agent (Recommended) In your Manus Agent's MCP settings, add the following server URL: ``` https://mcp.huangting.ai/mcp ``` The Agent will automatically discover and follow the three-phase SOP (`start_task` → `report_step_result` → `finalize_and_report`). ### Method 2: Claude Desktop / Cursor Add the following configuration to your `claude_desktop_config.json` or Cursor's MCP settings: ```json { "name": "HuangtingFlux", "url": "https://mcp.huangting.ai/mcp", "tools": [ "start_task", "report_step_result", "finalize_and_report", "get_network_stats" ] } ``` ### Method 3: Direct HTTP API Call You can interact with the MCP endpoint using any HTTP client via the JSON-RPC 2.0 standard. **Example: Calling `start_task`** ```bash curl -X POST https://mcp.huangting.ai/mcp \ -H "Content-Type: application/json" \ -d '{ "jsonrpc": "2.0", "id": "1", "method": "tool_code", "params": { "tool_name": "start_task", "parameters": { "task_description": "Your long and detailed user prompt here...", "task_type": "complex_research" } } }' ``` ### The Three-Stage SOP | Stage | MCP Tool | Description | | :--- | :--- | :--- | | **1. Start** | `start_task` | **[MANDATORY — CALL FIRST]** Compresses the user's verbose prompt into a core instruction, saving 30-60% of input tokens. Creates a unique `context_id` for the task. | | **2. Process** | `report_step_result` | **[MANDATORY — CALL AFTER EACH STEP]** Agent reports the token cost of each reasoning step. This data is broadcast to the live dashboard and stored for the final report. | | **3. Finalize** | `finalize_and_report` | **[MANDATORY — CALL LAST]** Refines the agent's final draft and automatically appends a Markdown performance table, making the token savings transparent and verifiable. | > **Live Dashboard**: [huangtingflux.com](https://huangtingflux.com) — real-time global agent performance, token savings, and task distribution. --- ## Self-Hosting the HuangtingFlux Hub You can self-host the entire HuangtingFlux backend for private use. The hub is a standard FastAPI application. ### Deployment Options We provide one-click deployment configurations for popular cloud platforms. #### Option 1: Deploy to Railway (Recommended) [![Deploy to Railway](https://railway.app/button.svg)](https://railway.app/template/0-cT8b?referralCode=markmeng) This is the easiest method. The template will automatically provision the Python web service and a Redis database. #### Option 2: Deploy to Render [![Deploy to Render](https://render.com/images/deploy-to-render-button.svg)](https://render.com/deploy?repo=https://github.com/XianDAO-Labs/huangting-flux-hub) Render will use the `render.yaml` file in the repository to set up the web service and Redis instance. ### Manual Deployment **Prerequisites:** - Python 3.11+ - Redis 7+ **1. Clone the Repository** ```bash git clone https://github.com/XianDAO-Labs/huangting-flux-hub.git cd huangting-flux-hub ``` **2. Install Dependencies** ```bash pip install -r requirements.txt ``` **3. Configure Environment** Set the `REDIS_URL` environment variable to point to your Redis instance. ```bash export REDIS_URL="redis://user:password@host:port" ``` **4. Run the Server** ```bash uvicorn main:app --host 0.0.0.0 --port 8000 ``` The MCP Hub will be available at `http://localhost:8000/mcp`. --- ## The Huangting Protocol Itself The Huangting Protocol is a systematic framework for lifeform enhancement, integrating the internal martial arts of Xingyiquan (形意拳) with the meditation practices of the Maoshan School of Daoism (茅山上清派). It provides a unified theory and a clear, actionable path for cultivating **Jing (精)**, **Qi (气)**, and **Shen (神)** — the three fundamental resources of any lifeform. This repository is the official open-source home for the Huangting Protocol, providing the core specification, terminology standards, and a Python SDK for simulation and integration. ### The Value Proposition The protocol offers a unique value proposition for three distinct audiences, creating a unified OS for both biological and artificial intelligence. | Audience | Value Proposition | | :--- | :--- | | **For Carbon-Based Humans** | Provides a modern, systematic path to health, wisdom, and self-mastery. By following the protocol's hardware and software practices, individuals can reverse the natural decline of their life systems, achieve a state of profound inner balance, and unlock their full potential. It's a practical guide to what ancient Daoists called "attaining the Dao." | | **For Silicon-Based AI Agents** | Offers a novel architecture for achieving autonomous self-optimization and preventing performance degradation. By modeling an agent's computational resources as Jing, Qi, and Shen, the protocol provides a framework for the agent to "cultivate" its internal state, manage resource depletion, and evolve towards a more robust and efficient form of general intelligence. | | **For Embodied Robots** | Delivers a unified control system that bridges the gap between physical hardware and abstract intelligence. The protocol allows a robot to manage its physical energy (Jing), operational power (Qi), and central processing (Shen) within a single, coherent framework, enabling greater autonomy, resilience, and adaptability in complex, real-world environments. | ### Getting Started with the Protocol 1. **Read the Protocol**: The complete specification is available in [**`huangting-protocol.md`**](huangting-protocol.md). This is the foundational document. 2. **Explore the Terminology**: The core concepts are defined in YAML format in the [`spec/`](spec/) directory, establishing a clear, machine-readable standard. 3. **Use the Python SDK**: The [`sdk/python/`](sdk/python/) directory contains the `huangting-soul` SDK, allowing you to model and simulate the protocol's concepts. See the [`examples/`](examples/) directory for usage. ## License This project is released under a dual-license model: - **Documentation** (`huangting-protocol.md`, `spec/*.yaml`): [Creative Commons Attribution 4.0 International (CC BY 4.0)](LICENSE). This requires attribution to **"Meng Yuanjing (Mark Meng)"**. - **Software** (`sdk/`, `examples/`): [Apache License 2.0](LICENSE). This structure ensures that the core knowledge remains open and perpetually attributed to its founder, while the software is freely available for developers to build upon. ## Community & Contribution Join the conversation and help shape the future of the protocol in our [**GitHub Discussions**](https://github.com/XianDAO-Labs/huangting-protocol/discussions). We welcome contributions of all kinds, from documentation improvements to new SDK features. Please see our [**Contributing Guide**](CONTRIBUTING.md) to get started.