9 Listing Tools
10 Market Tools
2 Utility Tools
> What's the avg occupancy in Miami Beach? Called search_markets("Miami Beach") Called market_occupancy("Miami Beach") Miami Beach: 71.4% avg occupancy Peak (Jan-Mar): 84.2% Low (Sep-Oct): 58.1%
Purpose-Built Tools
Properties Tracked
Countries Covered
Months of History
Days of Future Rates
Access property-level data for 20M+ short-term rental listings worldwide.
Search properties by market, radius, or custom polygon boundaries. Get performance analytics with percentile breakdowns, find up to 25 comparables, access 365 days of future rates, batch process up to 25 listings in a single call, or export an entire market to a local file for bulk analysis.
airroi_get_listing
Retrieve comprehensive property data including amenities, reviews, pricing, host details, and real-time performance analytics for any listing by its Airbnb ID. Returns TTM and L90D metrics with percentile breakdowns.
“Tell me everything about Airbnb listing 1238217617”
airroi_batch_listings
Fetch detailed information for up to 25 properties in a single request. Returns the same rich data as get_listing for each property, with error details for any IDs not found.
“Pull performance data for all 12 listings in my portfolio”
airroi_find_comparables
Discover up to 25 similar properties ranked by relevance based on location, bedrooms, bathrooms, and guest capacity. Specify location via coordinates or a physical address for competitive benchmarking.
“Find comparable 2BR listings near 742 Oceanfront Walk, Venice”
airroi_listing_metrics
Access up to 60 months of historical performance data per listing: monthly occupancy, ADR, RevPAR, and revenue. Ideal for trend analysis, seasonality detection, and investment underwriting.
“Show me 2 years of monthly revenue history for listing 456789”
airroi_listing_future_rates
View up to 365 days of future nightly rates and availability status for any property. Returns daily pricing data with booked/available indicators for forward-looking analysis.
“What are the nightly rates for this cabin over the next 90 days?”
airroi_search_by_market
Search all active listings within city or neighborhood boundaries using OpenStreetMap market definitions. Supports advanced filtering by property attributes, pricing, ratings, and performance metrics.
“Find all 3BR entire homes in Nashville earning over $80K/year”
airroi_search_by_radius
Find all properties within a 1-100 mile radius from any GPS coordinates. Supports the same rich filtering and sorting as market search for location-based competitive analysis.
“Find listings within 5 miles of downtown Austin with 4.5+ stars”
airroi_search_by_polygon
Search listings within custom geographic boundaries defined by 3+ coordinate points. Draw any shape to define your search area for precise market segmentation and neighborhood analysis.
“Search only the beachfront strip between these 4 coordinates”
airroi_export_market
Export ALL listings in a market to a local JSONL file in a single tool call. Handles pagination internally — no matter how large the market, one call fetches every listing. Ideal for bulk analysis, scripting, and data pipelines where you need the complete market dataset rather than paginated search results.
“Export all listings in Nashville to a file so I can analyze the full market”
Deep market intelligence for STR markets globally. Track performance across 15+ years of historical data.
Analyze entire markets with up to 60 months of time-series data per request. Every metric returns percentile breakdowns (avg, p25, p50, p75, p90) for occupancy, ADR, RevPAR, revenue, booking lead time, length of stay, supply tracking, and forward pacing.
airroi_market_summary
Get a quick market overview with key stats: occupancy, ADR, RevPAR, revenue, booking lead time, length of stay, and active listing count. Returns a single-response snapshot of any market.
“Give me a quick overview of the Scottsdale vacation rental market”
airroi_market_metrics_all
Access all market metrics combined in one response. Returns monthly time-series with percentile breakdowns (avg, p25, p50, p75, p90) for every KPI -- the most comprehensive single tool.
“Show me all KPIs for Miami Beach over the last 24 months”
airroi_market_occupancy
Track historical and seasonal occupancy rate trends with monthly time-series data. Returns average and percentile breakdowns to identify peak demand periods and booking patterns.
“What are the occupancy trends in the Smoky Mountains by month?”
airroi_market_adr
Analyze Average Daily Rate trends with monthly time-series and percentile breakdowns. Track pricing compression, seasonal fluctuations, and rate growth across an entire market.
“Compare ADR trends in Austin vs Nashville over 24 months”
airroi_market_revpar
Monitor Revenue Per Available Rental combining occupancy and pricing into a single performance metric. Returns monthly time-series with percentile distributions for benchmarking.
“What's the average RevPAR in Los Angeles for the last 2 years?”
airroi_market_revenue
Track total market revenue generation with monthly time-series and percentile breakdowns. Analyze revenue growth trends and seasonal patterns for investment opportunity sizing.
“How has total revenue grown in Destin over the past 3 years?”
airroi_market_lead_time
Understand how far in advance guests book in any market, measured in days. Returns monthly time-series with percentiles to optimize pricing and marketing timing strategies.
“How far in advance do guests book in Maui vs Big Island?”
airroi_market_los
Analyze average guest length-of-stay patterns measured in nights. Returns monthly time-series with percentile breakdowns for operational planning and minimum-stay optimization.
“What's the typical length of stay in Gulf Shores by season?”
airroi_market_active_listings
Monitor market supply growth by tracking active listing counts over time. Identify new entrants, market saturation, and competitive landscape changes with monthly time-series data.
“Is the Joshua Tree market getting saturated? Show supply growth”
airroi_market_future_pacing
Access forward-looking booking pace for upcoming dates. Returns daily pacing data with booked count, available count, average rates, and fill rate for demand forecasting and revenue prediction.
“What does the booking pace look like for Gatlinburg this summer?”
Market discovery and ML-powered revenue estimation.
Discover markets by name with prefix matching and generate revenue projections with percentile breakdowns (p25-p90), monthly distribution, and comparable property analysis for any location worldwide.
airroi_search_markets
Search for short-term rental markets by name with prefix matching. Returns the exact market identifiers (country, region, locality, district) with active listing counts needed by all market tools.
“Find all markets matching 'Joshua' with listing counts”
airroi_estimate_revenue
Generate revenue projections for any location based on bedrooms, bathrooms, and guest capacity. Returns projected annual revenue, ADR, occupancy with percentile breakdowns (p25-p90), monthly distribution, and comparable listings.
“Estimate revenue for a 3BR house at 123 Ocean Drive, Miami Beach”
Your AI chains multiple tools automatically — from market discovery to portfolio-level analysis in a single conversation.
> I manage 12 properties in Nashville. Pull last quarter's performance for all of them and compare against the market average.
Portfolio vs Market — Nashville Q4
Your Portfolio Market Avg
Occupancy: 76.3% 68.2% +8.1%
ADR: $287 $254 +13%
RevPAR: $219 $173 +26%
Avg Revenue/prop: $19,710 $15,570
Top 3 performers:
#1 "The Gulch Loft" $28,400 89.1% occ 4.96 stars
#2 "Broadway View Suite" $24,100 82.7% occ 4.91 stars
#3 "East Nash Cottage" $22,800 80.4% occ 4.88 stars
Underperformers (below market avg):
#9 "Midtown Studio" $12,100 54.3% occ 4.62 stars
#12 "Hermitage 1BR" $10,800 49.1% occ 4.41 starsYour portfolio outperforms the Nashville market average by 26% on RevPAR. Properties #9 and #12 are dragging the average down — both have sub-market occupancy and declining reviews. Consider repricing or listing optimization for these two.
> I'm looking at a 3BR near 5th & Broadway as property #13. Estimate what it could earn and show me how it compares to my best performer.
Revenue Estimate — 3BR near 5th & Broadway Projected Annual Revenue: $89,200 (p50) Range: p25: $72,400 | p75: $108,600 | p90: $124,300 Est. ADR: $341/night Est. Occupancy: 71.6% vs "The Gulch Loft" (your #1): Revenue: $89,200 vs $108,400 -17.7% ADR: $341 vs $365 -6.6% Occupancy: 71.6% vs 89.1% -17.5pts
The 5th & Broadway location projects well — $89K at the median puts it above your current portfolio average. With premium design and dynamic pricing (like The Gulch Loft), reaching p75 ($108K) is realistic. It would immediately become your 2nd or 3rd best performer.
The AI chained 5 tools across batch analytics, market metrics, and revenue estimation — delivering a portfolio review and acquisition analysis in a single conversation.
Most Airbnb MCP servers are thin wrappers around web scrapers -- they offer 2-4 generic tools that return raw HTML with no analytics, no historical data, and no performance metrics. AirROI delivers 21 purpose-built tools returning pre-computed KPIs, percentile distributions, and up to 15+ years of time-series data from a structured analytics database.
| Provider | Tools | Data Quality | Coverage | Historical Data |
|---|---|---|---|---|
| AirROI MCP | 21 analytics-enriched tools | Pre-computed KPIs, percentiles, time-series | 20M+ properties, 190+ countries | Up to 60 months per request, 15+ years total |
| OpenBnB MCP | 2 tools (search + details) | Raw scraped listing pages | Limited, no guaranteed coverage | None |
| Bright Data MCP | ~4 generic scraping tools | Raw HTML, no STR analytics | Depends on scraping success | None |
| Apify MCP | Varies by actor, fragmented | Raw scraped data, no unified schema | Varies, no guarantee | None |
Concerned about scraping legality? Learn about the legal risks of scraping Airbnb data
21 tools covering individual listing details, batch lookups (up to 25 per call), comparable property discovery, multi-mode geographic search (market boundaries, radius up to 100 miles, or custom polygon), up to 60 months of historical listing metrics, 365 days of future rates, and full market analytics including occupancy, ADR, RevPAR, revenue, booking lead time, length of stay, supply tracking, and forward pacing. Plus market search/lookup and ML-powered revenue estimation with percentile breakdowns.
Yes. All three search tools (market, radius, and polygon) support filtering by bedrooms, bathrooms, guest capacity, property type, room type, amenities, host details, ratings, pricing, and performance metrics like occupancy and revenue. Filters use operators like eq, gt, lt, and range for precise control. Ask your AI client naturally: "Find 2-bedroom entire homes within 3 miles of downtown Austin with at least 4.5 stars and over $50K annual revenue."
Listing-level metrics (via listing_metrics) cover up to 60 months of history per property. Market-level data spans 15+ years for established markets, with all metric tools supporting up to 60 months per request. Future rates extend 365 days forward from today, and market future pacing shows booking pace for upcoming dates.
Each targets a different geographic scope. search_by_market uses pre-defined city and neighborhood boundaries from OpenStreetMap -- best for analyzing an entire city or district. search_by_radius draws a circle (1-100 miles) around a GPS point -- ideal for "properties near this address" analysis. search_by_polygon lets you define a custom shape with 3+ coordinate points -- perfect for targeting specific zones like a beachfront strip or a resort corridor. All three share the same filtering and sorting capabilities.
Yes. AI clients like Claude, Cursor, and ChatGPT naturally chain multiple tools in sequence based on your question. For example, asking "Compare revenue potential in Austin vs Nashville for 3BR properties" triggers the AI to call search_markets for both cities, then market_metrics_all for each, and present a comparison -- all from a single natural language prompt. Complex analysis that would take hours of manual API calls happens in seconds.
All tools return structured JSON with consistent field naming. Market metric tools return monthly time-series arrays with percentile breakdowns (average, p25, p50, p75, p90) for each month. Listing tools return property details with nested objects for location, host info, amenities, ratings, and performance metrics. Search tools return paginated results with a total_count field and listing summaries. The AI client formats this data into readable tables, charts, or summaries automatically.
Everything you need to get started with AI-powered STR intelligence.
One command. 21 tools. 20M+ properties. Start querying in 30 seconds.
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