Unlocking Investment Insights with AI: My Journey from Stocks to Real Estate
A while back, I developed a simple app to track stock data, turning it into a personal investment assistant. Its success led to broader applications in real estate, where I analyze:
- Neighborhood comparisons
- Flood risks and weather patterns
- School zones and property types
This complex decision-making process revealed the potential for AI agents. Instead of using traditional models like ChatGPT, I leveraged mcp-agent, allowing me to build a persistent, multi-agent system that pulls live data while remembering my preferences. Key components include:
- Orchestrator: Selects the optimal agent for specific tasks.
- EvaluatorOptimizer: Ranks and enhances results for quality.
- Elicitation: Integrates human feedback as needed.
- MCP Server: Offers API access for versatile usage.
Modular and model-agnostic, it works seamlessly with various AI frameworks.
I’m eager to hear your thoughts! Share your insights on AI’s role in investment.