MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
제작자가 쓴 설명(영어 원문)
Read-only analytics for short-term rentals: bookings, occupancy, forecasts, reviews, owner payouts.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://slipstream.rentals/api/ask/mcp터미널에서 이 명령어를 실행하세요
claude mcp add --transport http slipstream https://slipstream.rentals/api/ask/mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"slipstream": {
"url": "https://slipstream.rentals/api/ask/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"slipstream": {
"type": "http",
"url": "https://slipstream.rentals/api/ask/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://slipstream.rentals/api/ask/mcp메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
서버가 도구 목록을 보여 주기 전에 로그인을 요구해요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 도메인 slipstream.rentals 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
298ms 만에 응답(HTTP 401)
OAuth 로그인을 지원한다고 밝혀서, AI 앱이 로그인 화면으로 안내해 줘요
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 3개 중 3개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.0.1)은 8일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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