Real Estate Valuation Calculator
real_estate_analytics_mcp delivers precise property analytics for real estate investors and data analysts. Estimate property valuations instantly with calculate_valuation using square footage, bedrooms, bathrooms, and location score (1-10). Analyze any ZIP code's safety, schools, and walkability via get_neighborhood_stats, and compute gross/net rental yields with calculate_rental_yield from purchase price, monthly rent, and annual expenses.
Overview
The Real Estate Valuation Calculator server provides three tools—calculate_valuation, get_neighborhood_stats, and calculate_rental_yield—to estimate property values, retrieve ZIP-code neighborhood scores, and compute rental returns from basic inputs. Developers feed in details like square footage or ZIP codes to get dictionary outputs with breakdowns, enabling quick assessments without custom models or external APIs. This supports precise buy/sell/rent decisions directly in applications.
Key Capabilities
- calculate_valuation: Supply square footage, bedrooms, bathrooms, and location score (1.0-10.0, default 5.0); receive a dictionary with estimated value and itemized breakdown by size, features, and location.
- get_neighborhood_stats: Enter a 5-digit ZIP code; get a dictionary of safety, school quality, and walkability scores for area comparisons.
- calculate_rental_yield: Input property price, monthly rent, and annual expenses (taxes, insurance, maintenance); obtain gross yield, net yield percentages, and ROI in a dictionary.
Use Cases
- Property scouting: Run calculate_valuation on 2,000 sqft, 4 bedrooms, 3 bathrooms, location score 7.5 for a value estimate, then use get_neighborhood_stats on the ZIP to check safety and schools.
- Rental analysis: Apply calculate_rental_yield to a $500,000 property with $3,000 monthly rent and $12,000 expenses to confirm if net yield exceeds 5%.
- Portfolio ranking: Combine calculate_valuation and calculate_rental_yield across assets to prioritize by value and returns, or use get_neighborhood_stats to flag underperforming ZIPs.
- Market reports: Merge ZIP stats from get_neighborhood_stats with valuations for comparative tables in client reports or dashboards.
Who This Is For
Real estate developers, data analysts, and AI builders with intermediate Python or API experience. Ideal for integrating into investment apps, advisory bots, or analytics dashboards to deliver on-demand metrics.