HuangtingFlux — Huangting Protocol MCP Server

Registre officiel IA et agents

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

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

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

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  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

Questions fréquentes

Qu'est-ce que HuangtingFlux — Huangting Protocol MCP Server ?

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

Comment installer HuangtingFlux — Huangting Protocol MCP Server ?

Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport http huangtingflux-huangting-protocol-mcp-ser 'https://mcp.huangting.ai/mcp'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour HuangtingFlux — Huangting Protocol MCP Server ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

HuangtingFlux — Huangting Protocol MCP Server est-il open source ?

Son code est public sur GitHub, mais le dépôt ne déclare pas de licence standard.

Qui maintient HuangtingFlux — Huangting Protocol MCP Server ?

Il est publié par XianDAO-Labs. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.