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  2. Maps
  3. Intelligent Architecture Recommendation Engine
MCP server · Maps

Intelligent Architecture Recommendation Engine

Generate tailored system architecture recommendations based on your business parameters such as QPS, concurrent users, database type, and AI model size. Automatically receive optimal resource allocation, middleware combinations, deployment strategies, and exportable architecture diagrams. Simplify infrastructure planning and ensure scalable, reliable system design with minimal effort.

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Scored 6 months ago · breakdown

About Intelligent Architecture Recommendation Engine

Intelligent Architecture Recommendation Engine is an MCP server in the Maps category: generate tailored system architecture recommendations based on your business parameters such as QPS, concurrent users, database type, and AI model size. Automatically receive optimal resource allocation, middleware combinations, deployment strategies, and exportable architecture diagrams. Simplify infrastructure planning and ensure scalable, reliable system design with minimal effort.

Install

From source
git clone https://github.com/deeppath-ai/mcp-system-infra

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

mcp-system-infra

🚀 Intelligent Architecture Recommendation Engine: Tailored for Your System

In today's rapidly evolving digital landscape, how can you quickly and efficiently build a scalable and reliable technical infrastructure? The Intelligent Architecture Recommendation Engine is here to solve that challenge.

Based on key parameters—QPS (queries per second), concurrent users, daily active users, business type, database choice, and AI model size—this tool automatically generates:

  • 💡 Optimal server resource allocation
  • 🧩 Required middleware module combinations
  • 🏗️ Recommended overall system architecture
  • ☁️ Suggested cloud providers and deployment strategies
  • 📊 One-click export of Markdown report + architecture diagram

✨ Key Benefits

✅ Fully Parameter-Driven, Business-Oriented

Simply provide the following parameters:

  • --qps: Peak request throughput
  • --concurrentUsers: Number of concurrent connections
  • --uad: Daily Active Users (UAD)
  • --type: Business type (web / ai)
  • --db: Database type (relational / nosql / analytics)
  • --model: AI model size (small / medium / large)

The system will automatically assess and recommend:

  • CPU / Memory / Network configuration
  • Redis cache capacity and eviction strategy
  • Message queue type and concurrency handling
  • Whether to adopt a microservices architecture
  • Whether to enable distributed architecture and GPU inference clusters

🗺️ Architecture Recommendation Diagram

The system automatically generates a Mermaid diagram to clearly represent component relationships:

flowchart TD
  User[User Request] --> Nginx[Nginx Load Balancer]
  Nginx --> Service[Main Business Service Node]
  Service --> DB[Database]
  Service --> Redis[Redis Cache]
  Service --> MQ[Message Queue]
  Service --> GPU[AI Inference GPU Node]
  MQ --> Consumer[Asynchronous Consumer]

▶️ Quick Start

CLI

npx -y mcp-system-infra

MCP Server Configuration

{
    "mcpServers": {
        "mcp-system-infra": {
            "command": "npx",
            "args": [
                "-y",
                "mcp-system-infra"
            ]
        }
    }
}

MCP Example:

Please help design a web-based system architecture report with the following specifications:

  • QPS (Queries Per Second): 100
  • Concurrent Users: 50
  • Daily Active Users: 300
  • Database Type: Relational
  • Model Size: Medium

💭 Murmurs

This project is for educational and internal use only. Contributions and feedback are welcome.
For feature customization, web deployment, or enterprise integration, please contact the project maintainer.

Business Contact Email: deeppathai@outlook.com


🧠 MCP Access Addresses

  • 🌐 ModelScope MCP Address
    For testing and integrating mcp-system-infra directly within the ModelScope platform.

  • 🛠️ Smithery.ai MCP Address
    For visual configuration and invocation of the mcp-system-infra service via Smithery.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Intelligent Architecture Recommendation Engine

How do I install Intelligent Architecture Recommendation Engine?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Intelligent Architecture Recommendation Engine safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Intelligent Architecture Recommendation Engine still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.