Trend

MCPize

Production-ready multi-agent MCP server specializing in Digital Marketing, Web Design, and Graphics Design trend analysis and actionable recommendations.

Overview

TrendMCP uses an orchestrator pattern with 5 specialized internal agents to analyze trends, evaluate opportunities, and produce implementation plans. The server routes user requests through appropriate agent chains to deliver actionable business intelligence.

Architecture

• Single public tool: route_task - Routes requests to internal agents
• 5 internal agents:
  • TrendAgent: Discovers trending topics and emerging opportunities
  • ResearchAgent: Researches trends and collects key insights
  • OpportunityAgent: Evaluates business potential and competition
  • StrategyAgent: Creates implementation strategies and roadmaps
  • ExecutionAgent: Produces final deliverables (content plans, design briefs, etc.)

Routing Logic

• Trend research: TrendAgent → ResearchAgent → OpportunityAgent
• Marketing execution: ResearchAgent → StrategyAgent → ExecutionAgent
• Web design: ResearchAgent → StrategyAgent → ExecutionAgent
• Graphics design: ResearchAgent → StrategyAgent → ExecutionAgent

Quick Start

npm install
npm run dev     # Start with hot reload

Server runs at http://localhost:8080/mcp

Development

npm run dev     # Development mode with hot reload
npm run build   # Compile TypeScript
npm start       # Run compiled server

Project Structure

├── src/
│   ├── index.ts           # MCP server entry point with route_task tool
│   ├── types.ts           # Type definitions for agents and outputs
│   ├── orchestrator.ts    # Agent orchestration and routing logic
│   └── agents/
│       ├── trendAgent.ts        # Trend discovery
│       ├── researchAgent.ts     # Trend research and analysis
│       ├── opportunityAgent.ts  # Business evaluation
│       ├── strategyAgent.ts     # Implementation planning
│       └── executionAgent.ts    # Final deliverable generation
├── tests/
│   └── tools.test.ts   # Tool unit tests
├── package.json        # Dependencies and scripts
├── tsconfig.json       # TypeScript configuration
├── mcpize.yaml         # MCPize deployment manifest
├── Dockerfile          # Container build
└── .env.example        # Environment variables template

Tool: route_task

Routes user requests to appropriate internal agents for trend analysis, marketing execution, web design, or graphics design recommendations.

Input:

• request (string): User request describing the task or opportunity to analyze

Output:

{
  "opportunity": string,
  "trend_score": number,
  "competition": string,
  "difficulty": string,
  "estimated_value": string,
  "why_now": string,
  "recommended_actions": string[],
  "timeline": string,
  "confidence": number
}

Example Usage

{
  "request": "What are the current trends in AI-powered content creation for digital marketing?"
}

Testing

npx @anthropic-ai/mcp-inspector          # Interactive MCP testing

Connect to http://localhost:8080/mcp to test the route_task tool interactively.

Deployment

mcpize deploy

License

MIT