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HuangtingFlux — Huangting Protocol MCP Server

Official registry AI and agents

Reduces AI Agent token usage by 40% via three-stage SOP workflow.

Source code Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http huangtingflux-huangting-protocol-mcp-ser 'https://mcp.huangting.ai/mcp'
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "huangtingflux-huangting-protocol-mcp-ser": {
            "type": "http",
            "url": "https://mcp.huangting.ai/mcp"
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Huangting-Flux Hub
  2. MCP Integration Guide
  3. The Three-Stage SOP
  4. Self-Hosting
  5. Author
  6. License

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.

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

StageMCP ToolDescription
1. Startstart_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. Processreport_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. Finalizefinalize_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.

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

Frequently asked questions

What is HuangtingFlux — Huangting Protocol MCP Server?

Reduces AI Agent token usage by 40% via three-stage SOP workflow.

How do I install HuangtingFlux — Huangting Protocol MCP Server?

It runs as a remote server. In Claude Code: claude mcp add --transport http huangtingflux-huangting-protocol-mcp-ser 'https://mcp.huangting.ai/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.

Does HuangtingFlux — Huangting Protocol MCP Server need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is HuangtingFlux — Huangting Protocol MCP Server open source?

Its code is public on GitHub, but the repository does not declare a standard license.

Who maintains HuangtingFlux — Huangting Protocol MCP Server?

It is published by XianDAO-Labs. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.