Agents in code
The OpenAI Agents SDK connects to Streamable HTTP servers with custom headers. The server is stateless, so every tool call stands alone and retries are safe.
Agents SDK configAirbnb MCP use cases
AI Airbnb Market Analysis for Investors, Hosts and Managers
Real questions run against the live AirROI MCP server: the prompt, every tool call, the answer, and what it cost.
MCP protocol 2025-11-25Registry com.airroi/mcp
- Real sessions, run live
- 8
- Tool calls shown
- 19
- Roles covered
- 5
- Cost of every session combined
- $1.85
For short-term rental investors
Investors: screen markets before you buy
AI Airbnb market analysis works when the assistant reads real data.
Connected to the AirROI MCP server, Claude, Codex, Cursor or any MCP client can compare two cities for a 2-bedroom before you pay for inspections: trailing-12-month occupancy, ADR, RevPAR, revenue and supply for both, with the market and period named, for $0.42 in tool calls.
Screening is the slow part of buying. One arbitrage investor put it bluntly on X: everyone wants the $15K-a-month Airbnb screenshot, but “nobody wants the four-hour research that used to come before it.” Those hours go to rentalizer screens, spreadsheets and forum threads, repeated for every city on the list.
In the session here, Nashville 2-bedrooms out-earned Austin’s at almost the same occupancy, so the gap was rate, not demand. That is the answer that decides which market gets a site visit. For a specific address, follow up with a revenue estimate and the 25 nearest comps. That follow-up cost $0.30 in tool calls; the full session is in the Connect Claude to Airbnb data guide.
For short-term rentals, this is what a real estate MCP server looks like: the dataset behind the AirROI MCP server covers 20M+ Airbnb listings in 190+ countries. For long-term rents or MLS records, add a residential data server. Pressure-test the numbers with how to analyze an Airbnb market and the 7-metric due diligence checklist.
Investor brief
- Job
- Pick the market and the property before paying for inspections and an appraisal.
- Pain
- Hours of manual research per market, repeated for every city on the shortlist.
- Outcome
- A cited two-market comparison, including the supply you would compete against, for $0.42.
Investor
Compare two markets before you buy
Prompt
Compare Austin and Nashville for a 2-bedroom entire-home Airbnb: occupancy, ADR, RevPAR, annual revenue, and how many competing listings I'd face.
6 tool calls
airroi_search_markets$0.01query: Austin
airroi_search_markets$0.01query: Nashville
airroi_market_summary$0.10Austin, Texas, United States · room_type = entire_home · bedrooms = 2 · num_months: 12 · currency: usd
airroi_market_summary$0.10Nashville-Davidson, Tennessee, United States · room_type = entire_home · bedrooms = 2 · num_months: 12 · currency: usd
airroi_market_revenue$0.10Austin, Texas, United States · room_type = entire_home · bedrooms = 2 · num_months: 12 · currency: usd
airroi_market_revenue$0.10Nashville-Davidson, Tennessee, United States · room_type = entire_home · bedrooms = 2 · num_months: 12 · currency: usd
Answer written from these results
Over the trailing 12 months, 2-bedroom entire homes in Nashville earned more per listing: $40,075 in average annual revenue versus $24,965 in Austin. Occupancy is nearly identical (49% vs 48%), so the gap comes from rate: Nashville's ADR is $296 against Austin's $236, for RevPAR of $146 versus $114. Nashville also has less 2-bedroom supply, about 1,270 active listings a month versus about 2,029 in Austin. October 2025 was the strongest month for the median listing in both markets, at $5,009 in Nashville and $3,941 in Austin.
For hosts and co-hosts
Hosts: see where you rank in Airbnb search
Hosts can ask an AI assistant where listings rank in Airbnb search right now.
AirROI’s live search-ranking tool returns up to 270 listing IDs in the order Airbnb shows them for any map rectangle, so your assistant can find your listing and your comps in that order and tell you who sits ahead.
Visibility is the host’s blind spot. In a widely discussed r/airbnb_hosts thread, a host whose town has 1,596 active listings noted that Airbnb shows about 270 per search, so roughly 80% are effectively invisible unless a guest zooms into your exact street
. Replies added that results reshuffle between requests and vary by guest, so treat any ranking as a dated snapshot.
Ranking is its own question, separate from revenue. In the Gulch session here, only two of a condo’s 25 closest comps appeared at all, and neither was near the top. Re-run the same rectangle after a price, photo or title change and compare the two lists.
Host brief
- Job
- Know whether the listing is visible and priced in line with the comps guests see beside it.
- Pain
- Airbnb shows about 270 listings per search, and the rest are hard for guests to find.
- Outcome
- Your listing and your comps located in live rank order, for $0.20.
Host
See where listings rank in Airbnb search
Prompt
Where do listings rank in Airbnb search for the Gulch right now? Do any of my comps show up?
1 tool call
airroi_live_search_ranking$0.20bounds: south 36.144, west -86.793, north 36.16, east -86.774
Response excerpt (ranks 1–5 plus the two comps from the revenue-estimate example; 226 entries returned)
{ "count": 226, "results": [ { "listing_id": "54227245", "rank": 1 }, { "listing_id": "999063439555766914", "rank": 2 }, { "listing_id": "577434926565879835", "rank": 3 }, { "listing_id": "1778528959326730554", "rank": 4 }, { "listing_id": "1371243776626861688", "rank": 5 }, { "listing_id": "1142148268623294757", "rank": 86 }, { "listing_id": "29899487", "rank": 177 } ] }
Answer written from these results
Airbnb search returned 226 listings for this Gulch map rectangle, in rank order. Two of your 25 comps appear: "Walk to Meetings from Stylish Gulch Loft" at #86 and "Walkable Gulch Stay for Business Travelers" at #177. The other 23 weren't among the 226 results for this rectangle, either because they sit outside it or because search didn't surface them. The ranking is a live snapshot from the moment of the search.
Two related checks live on the tools page: a competitor’s live calendar with rates, open nights and cleaning fee, and a base price and nightly rate recommendation for your own listing. Neither publishes anything; you decide.
For property managers
Property managers: market context for owner reports
Property managers use the AirROI MCP server to write the market half of an owner report. Ask for 12 months of occupancy and ADR for the owner’s segment and the assistant drafts the section: peak months, soft months and how far rates swing.
Your PMS’s own MCP server supplies the owner’s actual bookings.
Owners ask the same question every month: was it us, or the market? Answering it means pulling benchmarks by hand for every owner, market and bedroom count. In the Scottsdale session here, one prompt returned a year of occupancy and ADR for 3-bedroom homes and turned it into a paragraph an owner can read.
Quarterly portfolio summaries work the same way. airroi_batch_listings pulls up to 25 listings in one call, airroi_listing_metrics returns up to 60 months of each one’s history, and the market tools supply the benchmark. To build the same report over the REST API, start with the custom STR market report guide and how property management software uses Airbnb data.
Property manager brief
- Job
- Monthly owner statements that explain performance against the market.
- Pain
- Benchmarks pulled by hand for every owner, market and bedroom count.
- Outcome
- A year of occupancy and ADR, written up as the market section, for $0.21.
Property manager
Write the market section of an owner report
Prompt
Draft the market section of my Scottsdale owner report: monthly occupancy and ADR for 3-bedroom entire homes over the last 12 months.
3 tool calls
airroi_search_markets$0.01query: Scottsdale
Response excerpt (first of 10 matches shown)
{ "entries": [ { "full_name": "Scottsdale, Arizona, United States", "country": "United States", "region": "Arizona", "locality": "Scottsdale", "district": "", "native_currency": "USD", "active_listings_count": 5589 } ] }airroi_market_occupancy$0.10Scottsdale, Arizona, United States · room_type = entire_home · bedrooms = 3 · num_months: 12 · currency: usd
Response excerpt
{ "market": { "country": "United States", "region": "Arizona", "locality": "Scottsdale", "district": null }, "results": [ { "date": "2025-09-01", "avg": 0.39, "p25": 0.17, "p50": 0.36, "p75": 0.56, "p90": 0.77 }, { "date": "2025-10-01", "avg": 0.48, "p25": 0.25, "p50": 0.49, "p75": 0.69, "p90": 0.84 }, { "date": "2025-11-01", "avg": 0.5, "p25": 0.32, "p50": 0.52, "p75": 0.69, "p90": 0.83 }, { "date": "2025-12-01", "avg": 0.5, "p25": 0.29, "p50": 0.5, "p75": 0.7, "p90": 0.84 }, { "date": "2026-01-01", "avg": 0.52, "p25": 0.31, "p50": 0.53, "p75": 0.74, "p90": 0.88 }, { "date": "2026-02-01", "avg": 0.64, "p25": 0.51, "p50": 0.69, "p75": 0.82, "p90": 0.92 }, { "date": "2026-03-01", "avg": 0.72, "p25": 0.6, "p50": 0.79, "p75": 0.9, "p90": 0.94 }, { "date": "2026-04-01", "avg": 0.54, "p25": 0.34, "p50": 0.56, "p75": 0.74, "p90": 0.87 }, { "date": "2026-05-01", "avg": 0.48, "p25": 0.24, "p50": 0.48, "p75": 0.7, "p90": 0.83 }, { "date": "2026-06-01", "avg": 0.46, "p25": 0.2, "p50": 0.43, "p75": 0.69, "p90": 0.85 }, { "date": "2026-07-01", "avg": 0.42, "p25": 0.16, "p50": 0.36, "p75": 0.66, "p90": 0.85 }, { "date": "2026-08-01", "avg": 0.39, "p25": 0.15, "p50": 0.37, "p75": 0.6, "p90": 0.77 } ] }airroi_market_adr$0.10Scottsdale, Arizona, United States · room_type = entire_home · bedrooms = 3 · num_months: 12 · currency: usd
Response excerpt
{ "market": { "country": "United States", "region": "Arizona", "locality": "Scottsdale", "district": null }, "results": [ { "date": "2025-09-01", "avg": 285.3, "p25": 219.8, "p50": 271.6, "p75": 331.1, "p90": 407.6 }, { "date": "2025-10-01", "avg": 331.8, "p25": 245.6, "p50": 310.8, "p75": 382.3, "p90": 479.7 }, { "date": "2025-11-01", "avg": 350.9, "p25": 263, "p50": 325.1, "p75": 403.7, "p90": 507.6 }, { "date": "2025-12-01", "avg": 369.8, "p25": 273.5, "p50": 334.1, "p75": 436.2, "p90": 538.5 }, { "date": "2026-01-01", "avg": 381.3, "p25": 285.8, "p50": 350.9, "p75": 441.9, "p90": 550.1 }, { "date": "2026-02-01", "avg": 449.4, "p25": 319.6, "p50": 408.3, "p75": 530.6, "p90": 676.7 }, { "date": "2026-03-01", "avg": 448, "p25": 326.1, "p50": 408.9, "p75": 522.8, "p90": 679.2 }, { "date": "2026-04-01", "avg": 394.1, "p25": 287.3, "p50": 366.1, "p75": 460, "p90": 585.5 }, { "date": "2026-05-01", "avg": 328.2, "p25": 237.7, "p50": 299.2, "p75": 384.7, "p90": 485 }, { "date": "2026-06-01", "avg": 284.5, "p25": 205.1, "p50": 255.6, "p75": 332.3, "p90": 438.7 }, { "date": "2026-07-01", "avg": 271.9, "p25": 195.3, "p50": 246.2, "p75": 316.5, "p90": 414.6 }, { "date": "2026-08-01", "avg": 266.3, "p25": 198.7, "p50": 237.5, "p75": 304.4, "p90": 411.6 } ] }
Answer written from these results
Scottsdale 3-bedroom entire homes peaked in March 2026 at 72% average occupancy (median 79%) and reached their highest ADR in February 2026 at $449. The softest months were September 2025 and August 2026, both at 39% occupancy, and ADR bottomed at $266 in August 2026. ADR runs highest from January through March ($381 to $449), and February's average was 69% above August's.
Pair AirROI with your PMS’s MCP server
An MCP client can hold several servers at once. Add your PMS’s server and AirROI’s to the same session in Claude, Codex, Cursor or another client, and the assistant pulls the owner’s reservations from one and the market benchmark from the other. Hospitable shipped the first official MCP server from a short-term rental platform in April 2026; Guesty’s is in beta.
Your PMS’s MCP server
Hospitable, Guesty and others
- Reservations and payouts
- Calendars and owner statements
- Your own account only
Some tools message guests
One session
Claude, Codex, Cursor or another client
- Calls each server by name
- Joins bookings to benchmarks
- Drafts the owner update
You review and send
AirROI MCP server
Market benchmarks
- Occupancy, ADR and RevPAR by month
- Forward pacing and comps
- Any market, any bedroom count
Can’t change listings or messages
Two-server prompts to try
For each property in my Hospitable account, compare this quarter’s occupancy with the AirROI market median for its bedroom count, and list the ones more than 10 points behind.
List my open weekends next month from Hospitable, then use AirROI’s forward pacing for the same market to show which of those weekends are filling fastest.
Hospitable’s own guide to MCP for Airbnb makes the split plain: there’s no official way to connect Claude or ChatGPT to Airbnb, so the PMS server reaches your account and a market-data server reaches the rest of the market. The Airbnb MCP servers compared page sets the kinds side by side.
Before you pair them
We haven’t published a recording of a two-server session; the prompts show the workflow, not a logged run. Hospitable’s server connects with OAuth, isn’t on its Essentials plan, and needs Mogul for owner-statement tools.
Some of its tools send guest messages immediately, so keep the rule one PMS builder put plainly: AI drafts, human sends.
No AirROI tool can change a listing, price, booking or message.
For revenue managers and analysts
Revenue managers: read demand ahead
Revenue managers use the AirROI MCP server to read demand that is already on the books.
The forward pacing tool returns each future night’s fill rate and booked rates for a market, so an assistant can flag high-demand dates weeks early and set them against lead time, stay length and ADR percentiles.
Pacing answers a narrower question than a forecast: how full is the market for each upcoming night, compared with the nights around it? A spike on one weekend usually means an event; a slow month means rate or minimum-stay changes are worth testing early. The full Gatlinburg session, with its daily rows, is on the Codex and ChatGPT page.
Read pacing next to how guests book: lead time says how far out the market fills, and length of stay says whether minimum-night rules fit demand. For rule matrices built on calendar evidence, see occupancy pacing; for the market-wide picture, AirROI’s summer 2026 booking pacing analysis.
Revenue manager brief
- Job
- Set rates and stay rules ahead of demand, not after it.
- Pain
- Pacing sits in one dashboard and historical benchmarks in another.
- Outcome
- Fill rate and booked rates by night, with the peak dates named, for $0.21.
Revenue manager
Read forward booking pace
Prompt
How is Gatlinburg pacing for the next few months? Show fill rate and booked rates for entire homes.
2 tool calls
airroi_search_markets$0.01query: Gatlinburg
airroi_market_future_pacing$0.20Gatlinburg, Tennessee, United States · room_type = entire_home · currency: usd
Answer written from these results
Across about 4,600 Gatlinburg entire homes, October 2026 is pacing at an average 36% fill rate, and the strongest nights so far are Friday and Saturday, October 9–10, at 49% and 52% filled. Booked October nights average $395. November averages 21% filled and December 17%, with December's booked nights averaging $453. Dates further out have little on the books yet: January through August 2027 average 5% or less.
Tools for reading demand
airroi_market_future_pacing$0.20Fill rate, booked and open listing counts, and average rates for each future night.
airroi_market_lead_time$0.10How many days ahead guests book, by month, from p25 to p90.
airroi_market_los$0.10Average stay in nights, by month, with percentiles.
airroi_market_adr$0.10ADR by month with p25, p50, p75 and p90 values.
For developers and agent builders
Developers: build STR agents without a data pipeline
Developers point any MCP-capable framework at
https://mcp.airroi.com with an X-API-KEY header and get 29 typed tools with JSON schemas. The agent reasons with search and market tools, writes bulk files with airroi_export, and pays per call at REST API prices.There’s no scraper, database or refresh job to run.
A builder on r/n8n chained five MCP servers (an Airbnb search scraper, web search, memory, charts and a calculator) to score cities for investment, and had to raise the agent’s iteration limit to 30. With pre-computed market metrics, one call returns what that chain had to assemble.
Bulk jobs stay out of the context window: airroi_export writes up to 100,000 listings to CSV or JSONL behind a 7-day download link, billed as one search call per 10 listings. Every call carries your API key, funded from a $10 minimum credit deposit. Prefer plain HTTP? The same data and key work over the AirROI REST API, with step-by-step API tutorials.
Workflows in n8n
The MCP Client Tool node takes the endpoint and a header credential, so an AI Agent node can pull market numbers on a schedule and post them wherever you like.
n8n setup stepsNotebooks with Codex
Codex in the ChatGPT desktop app, CLI or IDE calls the tools, then writes the CSV, the notebook and the chart straight into your repository.
Use Airbnb data in Codex and ChatGPTPrompt library
Prompts to copy
These twelve prompts cover the jobs above, each with the tools an assistant typically calls and what those calls cost at Standard prices. Swap in your market, address or listing IDs and paste them into Claude, Codex, Cursor or any MCP client.
Four were run word for word against the live server.
| Prompt | Who | Tools called | Cost | Copy |
|---|---|---|---|---|
| Compare Austin and Nashville for a 2-bedroom entire-home Airbnb: occupancy, ADR, RevPAR, annual revenue, and how many competing listings I'd face. | Investor |
| $0.42 | |
| Estimate annual revenue for a 3-bedroom, 2-bath home sleeping 8 at [address], then show the 25 nearest comps with their occupancy and ADR. | Investor |
| $0.30 | |
| Is [market] getting saturated? Show active listings by month for the last 36 months next to average revenue per listing. | Investor |
| $0.21 | |
| Where do listings rank in Airbnb search for the Gulch right now? Do any of my comps show up? | Host |
| $0.20 | |
| Show me listing [ID]'s nightly rates, open nights, minimum stay and cleaning fee for the next 30 nights. | Host |
| $0.20 | |
| How did July compare to last July for 2-bedroom entire homes in [market]? Give occupancy, ADR and revenue for both. | Host |
| $0.31 | |
| Draft the market section of my Scottsdale owner report: monthly occupancy and ADR for 3-bedroom entire homes over the last 12 months. | Property manager |
| $0.21 | |
| Pull these 12 listing IDs and summarize the last 90 days for each: occupancy, ADR and revenue against the market median. | Property manager |
| $1.10 | |
| From Hospitable, get last month's booked nights and revenue for [property]. From AirROI, get occupancy and ADR for 3-bedroom entire homes in its market for the same month. Draft the owner update; don't send it. | Property manager |
| $0.21 plus your PMS plan | |
| How is Gatlinburg pacing for the next few months? Show fill rate and booked rates for entire homes. | Revenue manager |
| $0.21 | |
| How far ahead do guests book in [market], and how long do they stay, month by month over the last 24 months? Flag months where lead time got shorter. | Revenue manager |
| $0.21 | |
| Export every 3-bedroom entire home within 5 miles of downtown Asheville to CSV, then chart trailing-12-month ADR against guest capacity. | Developer |
| $0.50 per 10 listings |
Every tool, parameter and price is listed under Airbnb analytics MCP tools. Setup steps for every client, from Claude and Codex to Cursor, VS Code and n8n, are in the Airbnb MCP setup guide.
Cost
What all eight sessions cost
Eight full analyses, from market comparisons to a pricing calendar, cost $1.85 together at Standard rates, all run against the live server. Each appears in full on exactly one page, with every tool call and a trimmed copy of each response.
- Recorded sessions
- 8
- Tool calls in total
- 19
- Total cost at Standard rates
- $1.85
| Session | Who | Calls | Cost | Full session on |
|---|---|---|---|---|
| Compare two markets before you buy | Investor | 6 | $0.42 | Airbnb MCP Server |
| Estimate a property's revenue and pull its comps | Host | 2 | $0.30 | Connect Claude to Airbnb Data |
| See where listings rank in Airbnb search | Host | 1 | $0.20 | This page |
| Check a competitor's live calendar | Host | 1 | $0.20 | All 29 Tools, With Prices |
| Size up a market outside the US | Investor | 2 | $0.11 | Airbnb MCP Servers Compared |
| Get a base price and nightly rates | Host | 2 | $0.20 | All 29 Tools, With Prices |
| Write the market section of an owner report | Property manager | 3 | $0.21 | This page |
| Read forward booking pace | Revenue manager | 2 | $0.21 | Codex & ChatGPT Setup |
| All eight sessions | 19 | $1.85 |
Calls start at $0.01, the same prices as the REST endpoints behind them; see per-call pricing for Preferred rates.
Frequently asked questions
They ask for the market context, and the assistant drafts it. For example: "monthly occupancy and ADR for 3-bedroom homes in Scottsdale over the last 12 months". That returned a March peak of 72% occupancy and a February ADR peak of $449, for $0.21. Add your PMS's MCP server for the owner's own bookings, and your assistant can write both halves of the report.
Yes. Give Claude, Codex or any MCP client your listing IDs. airroi_batch_listings pulls up to 25 at once, airroi_listing_metrics returns each listing's monthly performance for up to 60 months, and the market tools add the benchmark. A saved prompt turns it into a repeatable quarterly summary.
Yes. Hosts often say Airbnb shows only about 270 listings per search, so ranking decides visibility. airroi_live_search_ranking returns up to 270 listing IDs in live search order for any map area. Ask your assistant to find your listing and your comps in that list, then re-check after a price or photo change.
For short-term rental investing, yes. AirROI's MCP server estimates revenue for an address, pulls the 25 nearest comps and compares markets. A 2BR/2BA near 1000 Division St in Nashville came back at $52,600 a year (range $34,200–$65,900), against a comp median of $64,205. For long-term rental or MLS data, pair it with a residential data server.
It can read booking pace, which is the demand already on the books. airroi_market_future_pacing returns the fill rate and booked rates for each future night. In a real session, Gatlinburg entire homes were 36% filled for October, with October 9–10 at 49% and 52%. Use it to spot high-demand dates early.
They point an MCP-capable framework (OpenAI Agents SDK, n8n, Claude Agent SDK or their own client) at https://mcp.airroi.com with an X-API-KEY header. The agent gets 29 typed tools with JSON schemas, uses search and market tools for reasoning, and uses airroi_export for bulk data. Billing is per call, the same as the REST API.
Run your first analysis
Get an API key, add one URL to Claude, Codex, Cursor or any MCP client, and ask about any of 30,000+ markets. Calls start at $0.01, paid from a $10 minimum deposit.