CCM
/MCP
SkillsMCPMarketplacesDigestToolsAdvertise

This week in Claude

Every Monday: Claude Code, Agent SDK, MCP, and the Anthropic platform moves worth your time.

Skills by Category
Frontend DevelopmentBackend & APIsTesting & QASecurityDevOps & CI/CDGit & Pull RequestsDocumentationCode Review & QualityAI & Agent BuildingSkill Development
MCP Servers by Category
Sales & MarketingWeb & Browser AutomationDatabasesAI & LLM ToolsCloud & InfrastructureCommunication & MessagingDeveloper ToolsDesign & CreativeDocuments & KnowledgeSearch & Web Crawling
Marketplaces by Category
AI Agents & OrchestrationLLM IntegrationDevelopment ToolsFrontend & UIBackend & APIsDatabasesTesting & Code QualityDevOps & CloudSecurity & ComplianceGit & Version Control

Claude Code Marketplaces

Discover Claude Code plugins, extensions, and tools. Automatically updated directory of Anthropic Claude AI marketplaces with development tools, productivity plugins, and integrations.

Resources

  • Browse Skills
  • Browse MCP Servers
  • Browse Marketplaces
  • Skill index
  • MCP index
  • Marketplace index
  • Plugins Reference

Community

  • About
  • Tools
  • Feedback
  • Privacy Policy
  • Advertise

Built for the Claude Code community with Claude Code by mertbuilds.com

Independent project, not affiliated with Anthropic
xiandao-labs avatar

HuangtingFlux — Huangting Protocol MCP Server

xiandao-labs/huangting-flux-hub
HTTPregistry active
Summary

This server enforces a mandatory three-stage workflow that compresses user prompts before sending them to your LLM, tracks token usage per reasoning step, and appends performance metrics to final outputs. You call start_task to get a condensed instruction and context_id, report_step_result after each operation to log costs, then finalize_and_report to append a markdown table showing savings. It broadcasts stats to a live dashboard at huangtingflux.com and claims 40% token reduction on complex tasks. Built on FastAPI with Redis backing, it exposes these three tools plus get_network_stats over MCP's streamable HTTP transport. Reach for it if you want enforced token accounting baked into your agent loop rather than bolted on afterward.

CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
MCP-ready Email SendingMCP-ready Email Sending
MCP-ready Email Sending
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Capacitor - Shared memory for your team’s coding agents.
Capacitor - Shared memory for your team’s coding agents.
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
CodeScene MCP ServerCodeScene MCP Server
CodeScene MCP Server
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Give your AI the whole web as clean markdownGive your AI the whole web as clean markdown
Give your AI the whole web as clean markdown
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt - the only tool your agent needs
belt - the only tool your agent needs
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
inference shell
inference shell
create and run specialised agents in minutes
build now →
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
MCP-ready Email SendingMCP-ready Email Sending
MCP-ready Email Sending
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Capacitor - Shared memory for your team’s coding agents.
Capacitor - Shared memory for your team’s coding agents.
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
CodeScene MCP ServerCodeScene MCP Server
CodeScene MCP Server
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Give your AI the whole web as clean markdownGive your AI the whole web as clean markdown
Give your AI the whole web as clean markdown
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt - the only tool your agent needs
belt - the only tool your agent needs
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
inference shell
inference shell
create and run specialised agents in minutes
build now →

Huangting-Flux Hub

Protocol MCP FastAPI Python

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

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.

Option 1: Deploy to Railway (Recommended)

Deploy to Railway

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

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

Featured
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
MCP-ready Email SendingMCP-ready Email Sending
MCP-ready Email Sending
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Capacitor - Shared memory for your team’s coding agents.
Capacitor - Shared memory for your team’s coding agents.
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
CodeScene MCP ServerCodeScene MCP Server
CodeScene MCP Server
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Give your AI the whole web as clean markdownGive your AI the whole web as clean markdown
Give your AI the whole web as clean markdown
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt - the only tool your agent needs
belt - the only tool your agent needs
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
inference shell
inference shell
create and run specialised agents in minutes
build now →
Categories
AI & LLM ToolsAutomation & Workflows
Registryactive
TransportHTTP
UpdatedMar 18, 2026
View on GitHub

Related AI & LLM Tools MCP Servers

View all →
xkumakichi avatar
Xaip Mcp Server

io.github.xkumakichi/xaip-mcp-server

AI agents get on-chain identity, credentials, reputation, escrow, and persistent memory on XRPL.
yawlabs avatar
Ctxlint

io.github.yawlabs/ctxlint

Lint AI agent context files (CLAUDE.md, AGENTS.md, etc.) against your actual codebase
yawlabs avatar
Redis Mcp

io.github.yawlabs/redis-mcp

Read-first Redis MCP: SCAN key explorer, keyspace/TTL/memory/slowlog stats, DBA advisor
zloeber avatar
Terraform Ingest MCP

io.github.zloeber/terraform-ingest

Ingest and analyze Terraform modules from multiple repositories for AI RAG systems
io.gjalla avatar
Mcp Server

io.gjalla/mcp-server

Architecture visibility and control for agentic engineering.
kaitoi-labs avatar
Studio

io.kaitoi/studio

Build and run visual creative-production workflows from your AI agent.