implementation

Initialize Mastra AI Agent

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Linked challenge: Build a Supply-Price Momentum Agent

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Linked challenge

Build a Supply-Price Momentum Agent

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Initialize a Mastra AI agent in TypeScript. Define three tools: 'fetchPermitData' (querying Census BPS), 'fetchPriceIndex' (querying FHFA), and 'calculateDivergence'. Use the `Mastra` class to register these tools and define a basic workflow that sequences them. Show the imports from '@mastra/core'.

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Linked challenge

Build a Supply-Price Momentum Agent

In this challenge, you will architect a sophisticated real estate intelligence system using Mastra AI (TypeScript) to orchestrate data ingestion and automated machine learning workflows. You will focus on identifying 'divergent' housing markets where building permit growth (Census BPS) is failing to keep pace with home price appreciation (FHFA HPI). To optimize the forecasting component, you will integrate TPOT (Tree-based Pipeline Optimization Tool) via a Python bridge or microservice to automatically discover the best regression models for housing supply trends. The core of the challenge involves building a Mastra AI workflow that processes multi-geographic datasets, calculates momentum indicators, and utilizes an automated ML pipeline to predict future supply bottlenecks. You will define custom tools for the Mastra agent to query Census and FHFA APIs, then synthesize these signals into a 'Market Divergence Score' used by institutional investors to assess local market risk.

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