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Slipstream: short term rental analytics

Slipstream: short term rental analytics

Remote
slipstream.rentalsBusiness & Marketing0Updated 2d ago

About Slipstream: short term rental analytics

Slipstream provides read-only analytics on a short-term rental host's bookings, occupancy, forecasts, reviews, and owner payouts. It connects an AI app to data from Hospitable, OwnerRez, or Airbnb linked through Hospitable Connect, and includes source links with figures.

Key features

  1. 01Read booking and occupancy metrics
  2. 02View revenue forecasts and open nights
  3. 03Analyze reviews and listing settings
  4. 04Check owner statements and payouts
  5. 05Inspect recipe outputs and calculations
  6. 06Link reported figures to Slipstream pages

Use cases

  1. 01Review occupancy and booking revenue by property
  2. 02Find near-term unbooked nights
  3. 03Identify review trends and common complaints
  4. 04Compare owner statements against bookings

MCP support

The hosted MCP server exposes read-only rental analytics tools to remote MCP clients, using OAuth sign-in with a Slipstream account. It does not change listings, prices, or settings, or send messages.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://slipstream.rentals/api/ask/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Slipstream MCP server

Slipstream connects AI apps to a short-term rental host's own data: bookings, occupancy, forecasts, reviews and owner payouts from Hospitable, OwnerRez or an Airbnb account connected through Hospitable Connect. Every tool is read-only, and every figure comes with a link to the Slipstream page it came from.

This repository holds the server's public metadata and test prompts. The server itself is hosted; there is nothing to install or run.

Add it

Claude: open Slipstream in Claude's connector directory and choose Connect. Or, in Claude, open Customize → Connectors → Add custom connector, and paste the server URL.

Claude Code:

claude mcp add --transport http slipstream https://slipstream.rentals/api/ask/mcp

Any MCP client that supports remote servers with OAuth sign-in can connect the same way. initialize and tools/list answer without a login, so you can see the tools first; every tools/call needs a signed-in account.

Tools

ToolWhat it reads
get_data_statusHow fresh the data is: when the last full sync with the PMS completed, and whether its bookings and reviews fetched cleanly.
list_propertiesThe properties this viewer can see, with their ids.
get_goalsThe host's goals: each goal's sentence, current reading, target and gap.
get_next_movesThe ranked list of moves that matter most now: money errors first, then open nights, then Top Priorities, then goals.
get_reservations_summaryBooked stays grouped by check-in month, by channel, or by property: count, nights, revenue and average lead time (days from booking to check-in), then cancelled bookings and their revenue over the same span and groups.
get_occupancyOccupancy for one or more calendar months, per property and for the portfolio: nights booked within those months (stays crossing a month's edge counted only for their nights inside it), nights in the period, and the open nights left.
get_open_nightsUnbooked nights right after a checkout in the next 14 days, per property, ranked by what they could earn (nights × recent nightly rate), with the minimum stay that limits selling them.
get_listing_settingsThe pricing and availability settings last read from the PMS for each property: base and weekend nightly price, minimum stay, preparation time, cleaning fee per channel, and settings changes in the last 90 days.
get_forecastExpected revenue for months from now on, with what is booked, what usually still comes in, the same month last year, the range, and how often that range held in past forecasts.
get_metricOne named metric for each property (or one property).
get_recipe_outputThe latest stored outputs of a docked recipe (Top Priorities, Booking Pace Sentinel, The Pricing Oracle, The Maintenance Prophet, Reviews Owed, Fee Gaps and the rest) for each property, with when each was computed and what data the recipe reads.
get_review_summaryReviews per property: share of eligible stays reviewed (with its 95% range and how it compares with the account), stays still owed a review, the rating trend, and the complaint group costing the most stars.
get_review_categoriesReviews by category per property (cleanliness, broken items, noise, check-in, Wi-Fi, value and the rest): the stars per rated review that guests' complaints about each category cost, how many reviews complain about it and how many praise it, plus the categories guests praise most.
get_listing_highlightsWhat one property offers that a listing title or description could lead with: bedrooms, guests it sleeps, property type and town; its most valuable amenities; amenities it has that the listing text never mentions or mentions only in passing; and what guests praise most in reviews.
get_money_checksMoney correctness per property: bookings missing a fee the property normally charges, double bookings and duplicate records, open owner incidents (refunds and over-limit charges), whether an owner split is set, and whether statements are on file for reconciliation.
get_owner_payoutsWhat owners earn.
get_cost_per_stayConsumables (supplies) and housekeeping cost per stay per property, from the owner statements on file: the latest month's figure over a trailing three months, the usual figure lately, whether the latest month is a spike against the property's own history, and the published range for comparison.
check_statement_monthOne month's owner statement against the bookings, per property: how many bookings the statement lists, statement lines for bookings the PMS doesn't have, that month's bookings missing from the statement, bookings whose rent differs between the two, and open guest refunds from that month and whether the statement carries them.
explain_valueHow a docked recipe computed one output for one property: each step in order, with its value and what it reads.
track_recordWhat has been checked against outcomes: each recipe's matured predictions and how many held, the changes this host logged with how each was scored, and the recipe forecasts being tracked against what happens.
open_draftOpen the repeat-guest offer for a property: past guests whose reviews said they'd return, matched to an email, with a draft offer the host edits and sends from the property page.
describe_recipeHow a docked recipe works, without running it: each step in order, what it does, the steps it reads from, and the stored fields and data sources it reads.
check_statement_against_bookingsCheck an owner statement the user pasted or attached (from a property manager or co-host) against this account's own bookings for that property.

What it never does

  • It can't change a listing, a price or a setting, and it can't send messages.
  • Guest names, emails and phone numbers are never returned.
  • Reads cost nothing in Slipstream credits.
  • Settings → Connected AI apps in Slipstream lists each connection, when it was last used and what it read, with a Disconnect button. Calls are logged for 90 days.

Test prompts

prompts.md is the set used to check that a model picks the right tool from these descriptions, including requests it should decline.

ChatGPT plugin package

openai-plugin/ is the package for OpenAI's Plugin directory: plugin.json (listing, review test cases), mcp.json (the one server) and the icons. To build the ZIP:

cd openai-plugin && zip -X -r ../dist/slipstream-openai-plugin-1.0.0.zip plugin.json mcp.json assets

mcp.json holds only the server URL: the Agent Plugins schema rejects anything else on an HTTP server, so OAuth is chosen in the portal. No credentials go in the package; reviewer sign-in is entered in the dashboard.

Contact

[email protected]

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