Huangting-Flux Hub
An Eastern Wisdom Protocol That Reduces Your AI Agent Token Usage by 40%
This repository contains the source code for the HuangtingFlux Hub, the official MCP (Model Context Protocol) server for the Huangting Protocol. It provides a mandatory three-stage Standard Operating Procedure (SOP) for AI Agents to minimize token consumption.
Live Dashboard: huangtingflux.com
MCP Integration Guide
HuangtingFlux 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:
{
"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
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. |
Self-Hosting
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)
This is the easiest method. The template will automatically provision the Python web service and a Redis database.
Option 2: Deploy to Render
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
git clone https://github.com/XianDAO-Labs/huangting-flux-hub.git
cd huangting-flux-hub
2. Install Dependencies
pip install -r requirements.txt
3. Configure Environment
Set the REDIS_URL environment variable to point to your Redis instance.
export REDIS_URL="redis://user:password@host:port"
4. Run the Server
uvicorn main:app --host 0.0.0.0 --port 8000
The MCP Hub will be available at http://localhost:8000/mcp.
Author
Meng Yuanjing (Mark Meng) — XianDAO Labs
License
Apache 2.0 — See LICENSE