MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Beschreibung vom Entwickler (englisches Original)
Read-only analytics for short-term rentals: bookings, occupancy, forecasts, reviews, owner payouts.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:
https://slipstream.rentals/api/ask/mcpFühre das in deinem Terminal aus
claude mcp add --transport http slipstream https://slipstream.rentals/api/ask/mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"slipstream": {
"url": "https://slipstream.rentals/api/ask/mcp"
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"slipstream": {
"type": "http",
"url": "https://slipstream.rentals/api/ask/mcp"
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
ChatGPT verbindet sich nur mit Servern im Internet:
https://slipstream.rentals/api/ask/mcpMenünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Der Server verlangt eine Anmeldung, bevor er seine Tools auflistet.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde über die Domain slipstream.rentals bestätigt (die Registry prüft, wem die Domain gehört)
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Antwort in 298 ms (HTTP 401)
Gibt OAuth-Anmeldung an, damit deine KI-App dich zum Einloggen weiterleiten kann
Noch nicht geprüft; wir lesen die Tool-Liste, wenn wir den Endpunkt prüfen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 3 von 3 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.0.1) kam vor 8 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
In derselben Kategorie: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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.
https://slipstream.rentals/api/ask/mcp (streamable HTTP)rentals.slipstream/slipstream (server.json)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.
| Tool | What it reads |
|---|---|
get_data_status | How fresh the data is: when the last full sync with the PMS completed, and whether its bookings and reviews fetched cleanly. |
list_properties | The properties this viewer can see, with their ids. |
get_goals | The host's goals: each goal's sentence, current reading, target and gap. |
get_next_moves | The ranked list of moves that matter most now: money errors first, then open nights, then Top Priorities, then goals. |
get_reservations_summary | Booked 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_occupancy | Occupancy 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_nights | Unbooked 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_settings | The 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_forecast | Expected 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_metric | One named metric for each property (or one property). |
get_recipe_output | The 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_summary | Reviews 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_categories | Reviews 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_highlights | What 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_checks | Money 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_payouts | What owners earn. |
get_cost_per_stay | Consumables (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_month | One 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_value | How a docked recipe computed one output for one property: each step in order, with its value and what it reads. |
track_record | What 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_draft | Open 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_recipe | How 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_bookings | Check an owner statement the user pasted or attached (from a property manager or co-host) against this account's own bookings for that property. |
prompts.md is the set used to check that a model picks the right tool from these descriptions, including requests it should decline.
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.
concierge@slipstream.rentals