trend-mcp
Enables multi-agent trend analysis for digital marketing, web design, and graphics design, routing requests through specialized agents to produce actionable recommendations and implementation plans.
README
TrendMCP - Multi-Agent Trend Analysis Server
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
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