Dreambooth Studio

com.dreamboothstudio由 dreamboothstudio.com 發布官方發布者v0.1.0更新於 Oct 24, 2026

Ask about your Dreambooth Studio photobooths: sessions, revenue, credits, projects, device status.

已驗證Streamable HTTP可網頁執行資料與分析商業與電商媒體與設計

概覽

AI 產生的概覽

Dreambooth Studio 的遠端 MCP 伺服器,讓助理查詢照相亭營運者的場次、營收、額度與裝置狀態,並設計照相亭、相框和濾鏡。

可以做什麼
  • 查詢照相亭營運資料:場次與彙總(可依日期、亭子、付款狀態與管道篩選)、相簿媒體數量、依月份與付款管道的營收、AI 額度餘額、錢包流水,以及專案清單與裝置連線狀態。
  • 搜尋產品文件與常見問題。
  • 將目前對話連結到營運者帳號,並查看連結狀態。
  • 建立濾鏡,並在儲存前用範例照片預覽效果。
  • 在設計執行緒中生成相框、繼續調整,並儲存選定的結果。
  • 起草、調整、編輯並建立完整照相亭,也可複製既有的照相亭。
適用情境
適合 Dreambooth Studio 照相亭營運者想在對話中了解自家亭子的狀況——某台亭子忙不忙、賺了多少、裝置是否連線——或想用一句描述設計照相亭、相框、濾鏡而不必打開後台時使用。
執行需求
遠端端點,無需安裝。營運者透過連結工具以 Google 登入授權,或在用戶端本身的連線設定中登入。使用者不需設定權杖或環境變數。讀取資料需要已連結帳號,未連結時只能使用文件搜尋。
安裝前請注意
寫入類工具會建立真實物件:建立的照相亭會立即在公開連結上線,儲存相框或濾鏡會加入帳號。相框與照相亭生成會消耗帳號每日免費額度,並受 Studio 配額限制,反覆調整會持續消耗。寫入工具僅在 OAuth 登入方式下可用,較舊的裝置碼登入會被拒絕寫入。沒有刪除操作,也不涉及資金移轉,且沒有復原功能。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Dreambooth Studio,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.dreamboothstudio%2Fdreambooth/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "dreambooth-studio": {
      "type": "http",
      "url": "https://mcp.dreamboothstudio.com/mcp"
    }
  }
}

README

dreambooth-mcp

MCP server for Dreambooth Studio. Lets ChatGPT, Claude and Gemini answer an operator's questions about their own booths — "how did my Bandung booth do this week?" — by wrapping the Studio API the dashboard already uses.

Status: live at https://mcp.dreamboothstudio.com/mcp (server 0.3.0). Streamable HTTP + stdio, 23 tools — 13 read-only, 9 that create or edit something, and connect_account. Listed in the official MCP Registry as com.dreamboothstudio/dreambooth v0.1.0 (registry versions are immutable, so that entry stays at 0.1.0).

Ten tools are always registered, on stdio and on every HTTP session:

connect_accountstarts the device flow
readconnection_status · get_sessions · get_gallery_stats · search_docs
readlist_projects · get_project · get_revenue_summary · get_credits · get_wallet_transactions

session_info is an eleventh, registered only when MCP_DIAGNOSTICS=1.

Twelve more, listed on every connection (see below for what guards them):

createscreate_booth · start_booth · refine_booth · create_filter · duplicate_project
createsstart_frame · refine_frame · save_frame
editsupdate_booth_draft
readget_booth_draft · check_generation · preview_filter

Phase 3 hardening has since landed, on the OAuth path: the Studio runs a full OAuth 2.1 authorization server — PKCE S256 only, one-hour access tokens, 30-day refresh, dynamic client registration, RFC 8707 resource audience, RFC 7009 revocation, and a CSRF-bound consent screen that names the scopes being granted. This server is a protected resource in front of it (RFC 9728). Both discovery documents are live.

The device flow is the older path and keeps the older properties — its token is a year long, unscoped and unrevocable, so it must not be able to write. It cannot: the Studio refuses it with a 403 and a sentence naming the fix, exactly as it refuses a read-scoped OAuth token.

The tool list is the same on every connection. The twelve above used to be registered only when a request carried a bearer, which made tools/list answer 10 tools with no Authorization header and 22 with any string as one — the check was on the header's presence, not on anything in it. That is gone. An inventory that moves is unusable: the ChatGPT submission portal scans from the browser with no credential, so it could only ever see the read half while the submission declared all 22, and any client caching a pre-sign-in list keeps offering ten tools to an operator who has connected an account. What guards these tools now is what always decided the outcome anyway — AUTH_REQUIRED_TOOLS turns an uncredentialled call into the 401 that starts the OAuth flow, and the Studio's 403 answers a token without booths:write. There is no feature flag in this — an earlier version of this README described one, and it was removed; deploy order is what guards a new tool. See Connecting an account.

Design: docs/dreambooth-mcp-design.md in the Studio repo. Inline cards in ChatGPT: docs/apps-sdk-widgets-plan.md.


What it does not do

This service holds no database, no business logic, and no aggregations. Every tool wraps a route the Studio already exposes, so there is exactly one implementation of "what is this operator's revenue" and it lives in the Studio. The moment an aggregation is copied in here, it becomes a second source of truth that drifts silently — which is how you end up with three different revenue numbers and no way to tell which is right.

Also permanently out of scope: withdrawals, payout accounts, MFA/step-up, subscription token regeneration, and anything under /api/admin.

Run it

bash
npm installcp .env.example .env
npm run dev               # Streamable HTTP on PORT (default 8080)npm run dev:stdio         # stdio, for Claude Desktop
npm run buildnpm run inspect           # stdio smoke: handshake, tools/list, widgets, every toolnpm run inspect:http      # HTTP smoke: sessions, isolation, unknown-session 404npm run preview           # writes each widget state to .preview/ to open in a browser

inspect:http runs dist/, so npm run build first or you are testing the last build rather than your change.

Both smokes run without a token. search_docs needs no auth, and the authed tools must come back with a readable message naming connect_account rather than crashing — that failure path is part of what the checks verify.

Connecting an account

There is no token to configure, in either transport. The operator asks their assistant to connect; connect_account starts the device flow the Studio already runs for the Electron booth and returns a Google link for them to open (Google only: the Studio builds an accounts.google.com URL). A client that signs in through its own connector settings (a request with no session and no credential) gets use_client_sign_in and no link instead; that sign-in is the Studio's login page, which takes an email and password as well as Google. The tool returns immediately and polls in the background — a tool call that blocks for minutes reads as a hung server to every MCP client, and by the time they ask their next question the token is in place.

That includes local development. A pasted token would be a session-equivalent credential (one year, no scopes, no revocation) sitting in a file on disk, and in HTTP mode it would authenticate every incoming session as that one account. Approving in a browser after a restart takes about fifteen seconds; that is the whole cost of not having it.

Device-flow tokens are held in memory, per MCP session. A restart means everyone reconnects, which is the right trade for that path: there is no credential store to protect. The token itself is session-equivalent — one year, no scopes, no revocation — and that has not changed.

What changed is that it is no longer the only way in. A client that arrives with its own Authorization: Bearer is on the OAuth path, where the token expires in an hour, carries a scope the operator approved by name, and can be revoked at /api/oauth/revoke. Nothing is stored here on that path at all: the credential belongs to the request that carried it and is never written into a session, where a later request quoting the same session id could read it.

The two credentials are deliberately not equivalent in what they may do. The Studio refuses a non-GET from a device-flow token on any route that opted into connector writes — the weaker credential must not inherit access granted to the stronger one. Everything the booth fleet POSTs with that token is untouched. The write tools are still listed on a device-flow session, because the tool list must not depend on the credential; calling one there returns the Studio's 403 and its sentence, which tells the operator what to do instead.

Reading is unchanged on both: a session that never connects an account can read nothing but search_docs.

Deploy

Railway, following the dreambooth-whatsapp recipe: railway.json with npm run build / npm start, healthcheck on /health, restart ON_FAILURE. No Dockerfile, no CI, and no volume — this service is stateless.

Set DREAMBOOTH_API_URL and ALLOWED_HOSTS. There is no token to configure. Leave MCP_DIAGNOSTICS unset in production — see the tools section. OPENAI_APPS_CHALLENGE is set only while a directory submission is in flight — see docs/chatgpt-listing.md.

ALLOWED_HOSTS must list both public hostnames:

ALLOWED_HOSTS=mcp.dreamboothstudio.com,dreambooth-mcp-production.up.railway.app

Railway keeps serving its generated hostname after a custom domain is attached, and DNS-rebinding protection is an allow-list, not a filter — naming only one host makes the other return 400 on /mcp. /health keeps answering ok either way, because it is registered ahead of the transport, so the healthcheck cannot tell you this broke. Leaving the variable empty disables the protection entirely rather than allowing everything through some safer path.

Publishing to the registry

server.json is the registry manifest. Entries cannot be unpublished and each version is immutable — a changed URL or a fixed typo means publishing a new version, never editing the old one.

bash
./mcp-publisher validate server.json    # checks against the live registry, publishes nothing./mcp-publisher login dns --domain dreamboothstudio.com --private-key "$(openssl pkey -in key.pem -noout -text | grep -A3 priv: | tail -n +2 | tr -d ' :\n')"./mcp-publisher publish

Always validate first; it is the only step in that sequence you can take back.

The com.dreamboothstudio namespace is proved by a TXT record on the apex (dreamboothstudio.com, not the mcp subdomain), signed by key.pem. That file is gitignored and lives on one machine. Losing it is recoverable — generate a new Ed25519 pair and replace the TXT record. Leaking it is not: this repo is public, and whoever holds it can publish under com.dreamboothstudio/* permanently.

Connecting a client

The hosted server needs no install. In any client that accepts a remote MCP server, point it at:

https://mcp.dreamboothstudio.com/mcp

Claude Desktop

For running a local checkout — against a preview Studio, or a branch. To use the deployed server, add the URL above instead; there is nothing to clone.

Add to claude_desktop_config.json. --stdio is required — the entry point defaults to HTTP, and without it Claude Desktop starts a web server and waits forever for a reply on stdin.

json
{  "mcpServers": {    "dreambooth": {      "command": "npx",      "args": ["tsx", "src/index.ts", "--stdio"],      "cwd": "/absolute/path/to/dreambooth-mcp",      "env": { "DREAMBOOTH_API_URL": "https://dreamboothstudio.com" }    }  }}

Tools

ToolWrapsAuth
get_sessionsGET /api/sessionsBearer
get_gallery_statsGET /api/galleryBearer
search_docs/docs-search-index-{locale}.jsonnone
list_projectsGET /api/projectsBearer
get_projectGET /api/projects?id= + GET /api/device-monitoringBearer
get_revenue_summaryGET /api/me/revenue-summaryBearer
get_creditsGET /api/creditsBearer
get_wallet_transactionsGET /api/wallet-transactionsBearer

That is the complete read set. Two more wrap a route that creates something:

ToolWrapsAuth
create_filterPOST /api/filtersBearer + booths:write
duplicate_projectPOST /api/projects?duplicateBearer + booths:write
start_framePOST /api/ai/frames/start, then POST /api/ai/threads/{id}/messagesBearer + booths:write
refine_framePOST /api/ai/threads/{id}/messagesBearer + booths:write
check_generationnothing — reads this processBearer
save_framePOST /api/ai/frames/from-generationBearer + booths:write
preview_filterGET /api/filters/previewBearer (read is enough)
start_boothPOST /api/onboarding/generateBearer + booths:write
refine_boothPOST /api/onboarding/generate (regen, or a rebuild)Bearer + booths:write
create_boothGET /api/onboarding/draft → GET by-slug?checkOnly → POST /api/onboarding/draft-frames → GET /api/onboarding/frames + /catalog (+ /api/ai-effects/catalog) → POST /api/projects/onboarding → GET by-slugBearer + booths:write
get_booth_draftGET /api/onboarding/draftBearer (read is enough)
update_booth_draftPATCH /api/onboarding/draft (+ /api/ai-effects/catalog when an effect is named)Bearer + booths:write

Deploy order matters for the frame and booth tools. They are listed unconditionally — there is no flag — and they call Studio routes that are new or newly opened to OAuth: /api/ai/frames/start, /api/ai/frames/from-generation, /api/ai/threads/{id}/messages, /api/onboarding/generate, /api/onboarding/draft-frames, /api/projects/onboarding, /api/filters/preview. Deploy that Studio change before a build of this server that carries the tools, or the tools answer with a sentence saying the Studio is not updated yet. Booth generation also needs the Studio's digital_mode feature to be live (it is the /new pipeline; when dormant, the booth tools say so). oauth-write-check.mjs in the mcp-verify skill runs a real round — add --booth for the booth one — run it once after both are live.

Frame generation is the one flow here that is neither a single call nor a single answer. An image-model round trip runs 30–90 seconds against a 15-second request timeout in this service, and raising the timeout would not help: a tool call that blocks that long reads as a hung server to every MCP client. So start_frame and refine_frame start the work and return a job id, and check_generation reports — the shape connect_account already uses for the device flow. And one prompt rarely lands, so the flow is the dashboard's Frame Studio thread: start_frame opens a thread on a blank template and makes the first version, refine_frame makes the next one in the same thread ("darker", "less ornament"), and only save_frame turns the generation the operator chose into a frame in their list. Until then nothing is saved, and the tool descriptions, the results and the preview card all say so rather than leaving a model to guess. Every generation spends part of the account's free daily allowance, which is why the descriptions tell the model never to iterate on its own initiative.

Booths follow the same shape, through the /new onboarding pipeline — the Studio designs a whole booth from a sentence (spec, welcome screens for phone and laptop, in-booth background) and creates it. start_booth makes a DRAFT (a draftId, 60–120 s, a background job); refine_booth redraws the welcome screen or the in-booth background from an instruction, or rebuilds the whole draft from a new description; update_booth_draft changes what a redraw cannot — title, link name, button text, colours, capture mode, language, which frames and filters it carries, its AI effect, and the page settings the dashboard editor offers (photo count, countdown, timeouts, GIF/recording, retake, checkout, payment, result) — stored on the draft and applied by the Studio at create; get_booth_draft reads the draft back once the job store has forgotten it (drafts live 7 days); create_booth is the only step that makes a booth — it checks the link name first, draws the booth's own three frames, picks three starter frames and the Studio's default filter the way /new does, and creates the booth with the draft's design, theme and capture mode. The draft id is a plain value the model keeps, so a conversation outlives this process; drafts last seven days in the Studio. Quotas are the Studio's: 3 full generations and 5 redraws per draft, 10 drafts an hour per account. There is no spec-patch path — title, headline, colours change only through a redraw or a rebuild; title and link name are chosen at create time.

Filters are previewed before they exist: preview_filter asks the Studio to bake its sample photo (or the operator's own preview photo) through the booth's real filter pipeline and returns a URL; create_filter saves the same adjustments. The preview shows 13 of the 31 adjustments and says which it cannot — the booth applies all of them.

Jobs live in this process, keyed by a hash of the bearer that started them — never the bearer itself, which would mean holding operator credentials for as long as the jobs. A restart loses running jobs and the poll says so, pointing at the dashboard rather than reporting a failure that may not have happened. Running a second instance would break polling; the fix at that point is a shared store.

It generates onto the Studio's blank templates (layout + shape, resolved server-side), never at a width, a height or a photo window the model chose. drawParams is the contract the booth prints against, and invented geometry produces a frame that is created successfully and prints wrong — a failure that reports nothing. The saved frame's photo windows are keyed transparent by the same server code the /new onboarding flow uses.

They are listed everywhere and usable only on the OAuth path. Writing requires a credential that expires in an hour, carries a scope and can be revoked; the device flow's token is one year, unscoped and unrevocable, and must not inherit access granted to the other one. That rule is enforced where it can actually be evaluated — by the Studio, which holds the key to the next-auth JWE this server cannot read a scope out of. See utils/resolveAuthSession.ts there, and docs/write-tools-plan.md. Until 2026-09-23 it was also approximated here, by registering these tools only when a request carried a bearer; that made the tool list depend on an HTTP header and was removed.

Nothing deletes and nothing touches money. There is no put or delete on StudioClient; the Studio opened exactly eight POST handlers to it — /api/filters, /api/projects, /api/projects/onboarding, /api/onboarding/generate, /api/onboarding/draft-frames, /api/ai/frames/start, /api/ai/frames/from-generation, and /api/ai/threads/{id}/messages.

One thing does edit: update_booth_draft PATCHes /api/onboarding/draft, the single patch on StudioClient. It changes a draft that has not become a booth yet — drafts live 7 days and create_booth is still the only step that makes a real booth — but "nothing edits" stopped being true when it shipped.

Two tools wrap nothing: connection_status (is this session authenticated — polled by the connect card) and session_info (diagnostics, temporary, and registered only when MCP_DIAGNOSTICS=1; delete it once the session-continuity question in the widgets plan is answered).

Every tool carries a title, an outputSchema, and explicit readOnlyHint / destructiveHint / openWorldHint annotations. That is not decoration: both the Anthropic Connectors Directory and the ChatGPT plugin directory flag a tool that is missing any of them, and session_info is gated off by default because a listing is judged on its tool list and that one answers nothing an operator asked.

Output schemas are deliberately permissive — every field the Studio owns is optional. The SDK validates structuredContent against the schema and throws McpError on a mismatch, which is a protocol error, and rule 5 below exists to prevent exactly that. A Studio rename must degrade to a missing key, never to a broken tool.

Inline cards (ChatGPT)

connect_account renders a real card — a Google button that notices when the operator has finished approving — instead of a URL they have to copy. It is an MCP resource (ui://widget/connect-account.html) pointed at by _meta on the tool, per the Apps SDK.

duplicate_project renders a second card, ui://widget/write-result.html. It renders the result and nothing else: the copy's name, what it was copied from, and a link to it in the dashboard. There is no confirmation card and no form — a widget only renders after the tool has already written, so confirming would need a second tool that writes nothing, and the host's own approval dialog is the real gate. There is no "undo" button either: undo means PUT or DELETE, which would widen the scope from "create" to "change and delete" for one button. Its CSP names no origin at all, which is what makes it impossible for it to talk to the network.

Everything generated renders in a third card, ui://widget/generation.html — the one card whose CSP names an origin, because it shows images from the Studio's storage. From the moment a thing is asked for to the moment it exists:

  • start_frame / refine_frame / start_booth / refine_booth / create_booth return while the work runs, and their card is live: a skeleton of the thing being made (a strip with its photo windows, a phone with a welcome screen) that polls check_generation from inside the iframe every few seconds and redraws as the preview when the work is done — the operator watches it appear. check_generation is widget-accessible for exactly that; a host without callTool just leaves the card at "working".
  • check_generation shows the preview (frame image; booth draft with its welcome screen and palette; created booth with its thumbnail and links). get_booth_draft and update_booth_draft render the same draft card, with what was set and what could not be applied named on it.
  • save_frame shows the saved frame's thumbnail; create_filter shows the created filter on the Studio's sample photo (the same render preview_filter shows, fetched after the save — best-effort); preview_filter shows the preview and names the adjustments it cannot show.

Leaving a card goes through the host. Every https link in a card is routed through window.openai.openExternal (where the host has no such API the anchor keeps its own target="_blank"), and once the thing exists the whole card is the link: a created booth opens its public link, a saved frame, a created filter or a duplicated booth opens the dashboard. Drafts, previews and live cards are deliberately not links — nothing exists yet to open.

Nothing about this changes other clients. Every tool result carries the payload twice: structuredContent for widgets, and the same object pretty-printed as text content for Claude and Gemini, which render no widget. The text block is what it always was.

Widgets are self-contained HTML with an empty CSP on both domain lists. That is load-bearing: a card that cannot reach the network cannot leak the operator's session token, and it never needs to, because all of its data arrives through callTool on the server side. Keep it that way — inline any asset you need.

Design tokens are copied by hand into src/ui/tokens.ts from the Studio's tailwind.config.js, because a sandboxed iframe has no Tailwind. That makes it a second copy of the design system; when a brand colour moves, it moves there too.

get_project reports livenessTier, not the device's isOnline field. isOnline is retained only for back-compat and collapses "quiet because it was deliberately shut down" into "offline" — which is how a healthy fleet gets reported as broken.

The first three needed no Studio change at all. The rest depend on Studio work that has now landed: GET on /api/projects, /api/credits and /api/wallet-transactions accepts Authorization: Bearer via resolveAuthSession (PUT and DELETE deliberately still do not, and POST only on the two routes named above, only for a token carrying booths:write), and GET /api/me/revenue-summary is a new owner-scoped endpoint — /api/analytics/revenue is superadmin-gated and returns 403 to an operator.

get_wallet_transactions and get_revenue_summary answer different questions and their descriptions say so. The wallet ledger excludes cash and voucher income entirely, so for an operator who takes cash it understates real revenue — a model that reports it as "your earnings" is confidently wrong.

Identity is never an argument. No tool accepts a userId or email — the operator is resolved server-side from the token, exactly as lib/ai-chat does in the Studio. A tool that needs such an argument is designed wrong.

Rules for adding a tool

  1. It wraps an existing Studio route. If no route fits, add a thin one in the Studio — do not reimplement the query here.
  2. The description says when to call it, not just what it returns. The model picks tools by description alone.
  3. Return the smallest useful shape. get_gallery_stats returns counts, not 12 media URLs, because the model does not need them and they cost context.
  4. Read-only tools carry annotations: { readOnlyHint: true } so clients can auto-approve them. A write tool must not, and must also state idempotentHint — create_filter says false, because calling it twice makes two filters and a client that retries a timeout needs to know that.
  5. ownerEmail is not an argument. The Studio's POST handlers accept it for the dashboard's collaborator path. A tool that forwards it hands the caller a way to write into somebody else's account, so tool bodies are built field by field rather than spread from args. The Studio refuses it from a bearer as well; both halves are deliberate.
  6. Failures go back as isError content with a sentence the model can relay — never a protocol error, which just makes clients retry. For a write, relay the Studio's own message: "this connection is read-only, reconnect and approve permission to create things" names the button to press.

Notes

  • stdout is the transport. A single console.log corrupts the stream and the client drops the connection with a parse error. Diagnostics go to stderr.
  • Do not copy dreambooth-whatsapp's habit of committing .env. Nothing secret belongs in it here, and the surest way to keep that true is to never start.

來源:README.md,提交 282ca62

工具

22

connect_account

Connect a Dreambooth account

Connect this conversation to the person's Dreambooth Studio account. The answer's status says what happened. already_connected: an account is connected; nothing to do. awaiting_approval: it returns a link the person opens in their own browser to sign in with Google and approve. A Google account with the same email as an existing Dreambooth account connects that account. Ask them to open it and say when they are done; do not call this tool again while waiting. use_client_sign_in: this client connects accounts through its own app or connector settings, where they can sign in with an email and password or with Google, so no link is returned. Ask them to connect Dreambooth there (the client also asks by itself when a tool needs an account), then repeat their question. Either way, someone who has no Dreambooth account yet gets one when they sign in. Call this when another tool reports that no account is connected, or when someone asks to connect or switch accounts.

無需輸入參數。

connection_status

Check Dreambooth connection

Whether this conversation currently has a Dreambooth account connected, and which one. Call this if you are unsure whether to run connect_account first. Cheap and read-only — it does not contact Dreambooth.

無需輸入參數。

get_sessions

Get photo sessions

List the photo sessions recorded on this operator's booths, with totals. Call this when the operator asks how busy a booth has been, how many sessions ran in a period, or wants to inspect individual sessions. Supports date ranges, per-booth filtering, payment status and payment channel. For money totals rather than session counts, use get_revenue_summary instead.

輸入參數limitendDatestartDateprojectIdspaymentSourcesessionStatustransactionStatus

search_docs

Search Dreambooth documentation

Search the Dreambooth Studio documentation and FAQ. Call this before answering any question about the product, hardware, printing, booth setup, guest payments, or troubleshooting — answer from the docs rather than from memory. Pages about Dreambooth's own plans and billing come back as a link only: share the link, and do not quote prices, plans or trials in the conversation. Works without a connected account.

輸入參數limitquery必填locale

list_projects

List booths

List the photobooth projects this operator owns, with id, name, public link slug, whether it is active, and its currency. Call this first whenever the operator names a booth — you need the project id to filter any other tool by booth. Does not return booth designs or page layouts.

無需輸入參數。

get_project

Get one booth in detail

Full detail for a single booth: its name, public link, currency, screen size, and the live status of the device running it — whether it is online, when it was last seen, app version, and camera/printer/internet state. Call this when the operator asks about one specific booth, or whether a booth is working. Get the project id from list_projects first.

輸入參數projectId必填

get_revenue_summary

Get revenue summary

Business revenue from this operator's photobooth sessions across EVERY payment channel — gateway payments, cash vouchers (cash collected at the booth) and discount vouchers — grouped by month or day and by currency, with extra-print revenue and AI-effect purchases reported separately. Use this for any question about income, revenue or omzet. It is also the right tool when wallet earnings look too small: cash and voucher money never reaches the wallet ledger, so for operators who take cash the wallet figure legitimately understates income.

輸入參數tofromgroupBy

get_credits

Get AI credits and plan

This operator's remaining AI credit balance and their current subscription plan, including when it ends. Call this when they ask how many credits are left, whether they can still run AI effects, or what plan they are on. Credits are separate from wallet money — do not confuse the two.

無需輸入參數。

get_wallet_transactions

Get wallet transactions

This operator's wallet ledger: gateway earnings, withdrawals and refunds, newest first. Use for questions about the wallet, payouts or withdrawals. Do NOT use it to answer 'how much did I earn' — the wallet excludes cash and voucher income entirely, so for operators who take cash it understates real revenue. Use get_revenue_summary for income.

輸入參數tofromlimit

create_filter

Create a photo filter

Create a new photo filter on this operator's account from a description of the look they want — 'warm and slightly faded', 'high contrast black and white'. Translate the description into the adjustment numbers yourself; the ranges are in the schema. Call this only when the operator asks for a filter to be CREATED. It does not change an existing filter, and there is no tool that does — to edit or delete one, send them to the dashboard. Creating the same filter twice makes two filters, so do not retry a call that may have gone through.

輸入參數name必填isPublicadjustments必填

duplicate_project

Duplicate a booth

Copy one of this operator's existing booths, with all of its settings, into a new one. Use it when they want another booth 'like' one they already run — a second location, a one-off event, a variant to experiment on. Call list_projects first to get the project id; the operator will name the booth, not its id. The copy is named after the original and is not published at the original's public address, so it is safe to make and they can rename it in the dashboard. To design a NEW booth from a description, use start_booth instead of this; there is no tool that edits or deletes a booth that already exists.

輸入參數projectId必填

start_frame

Start designing a photo frame

Start designing a new photo frame for this operator's booths from a description of the look they want — 'batik motifs in warm gold', 'minimal Scandinavian, lots of white space'. It opens a design thread and makes the FIRST version. It returns immediately with a job id; call check_generation to see the result, and do NOT describe the frame as made until that says so. The result is a preview in the thread — nothing is in the operator's frame list until save_frame is called with the generation they choose. To change a result, call refine_frame with the threadId that check_generation returns, rather than starting again. Every generation spends part of the account's free daily allowance, so do not call this speculatively, twice for the same request, or while another generation is still running.

輸入參數shapelayout必填prompt必填

refine_frame

Refine a photo frame design

Ask for a changed version of a frame in an existing design thread — 'darker', 'less ornament', 'make the flowers smaller', 'more gold'. Call it with the threadId that check_generation returned for start_frame, and ONLY when the operator asks for a change: every call spends part of the account's free daily allowance, so never iterate on your own initiative. It returns immediately with a job id; call check_generation for the new preview. Earlier versions in the thread stay available to save_frame, so a change the operator dislikes loses nothing.

輸入參數prompt必填threadId必填

check_generation

Check background work

Report on background work started by start_frame, refine_frame, start_booth, refine_booth or create_booth. Always pass the jobId that the start/refine/create call returned — keep it for the rest of the conversation, because an id keeps working for the full 15 minutes even if the connection re-authenticates partway through, and calling with no arguments does not. With no arguments it reports the most recent job of any kind, which is a convenience for when the id was lost, not the normal way to call it. Designing a booth takes 1-3 minutes, a redraw about a minute, creating a booth 2-6 minutes: tell the operator that, then poll about every 15 seconds. While it says 'running', nothing exists yet — relay the progress line if there is one, tell the operator it is still going, and wait 10-15 seconds before calling again rather than polling tightly. When it says 'done': a frame job carries imageUrl, threadId and generationId (a preview — nothing saved until save_frame); a booth design carries draft{…} (a draft — nothing created until create_booth); a booth creation carries booth{slug, boothUrl, projectId} — the one case where something now exists. This reads a status and creates nothing, so it is always safe to call.

輸入參數jobId

save_frame

Save a generated frame

Save one generation from a design thread as a real frame in this operator's frame list, with its photo windows cut out. Call it only when the operator has chosen a result — pass the threadId and generationId that check_generation returned for it. This CREATES a frame: saving the same generation twice makes two frames, so do not retry a call that may have gone through. The frame is private to the account unless the operator explicitly asks for it to be shared. After saving, the operator picks the frame in a booth's frame settings; this tool does not assign it to a booth, and there is no tool that edits or deletes a frame.

輸入參數nameisPublicthreadId必填generationId必填

preview_filter

Preview a photo filter

Show what a filter would look like BEFORE creating it: the Studio renders its sample photo (or the operator's own preview photo, if they set one in the dashboard) through the exact pipeline the booth uses, and returns an image URL. Free and read-only — call it whenever the operator is designing a filter, adjust the numbers from their reaction ('warmer', 'less contrast'), preview again, and call create_filter with the same adjustments only once they are happy. Some adjustments (shadows, highlights, whites, blacks, clarity, dehaze, vibrance, texture) are applied by the booth but cannot be shown here; the result lists them as notPreviewed so you can say so. Nothing is created by this tool.

輸入參數adjustments必填

start_booth

Design a new booth

Design a complete photobooth (a 'booth') for this operator from a description — the Studio designs the welcome screen for phone and laptop, the in-booth background, the colour theme, the capture mode, a title and a link name, exactly as dreambooth.app/new does. Before calling, gather in chat what /new would ask and put ALL of it in the prompt: the occasion or business, the vibe or style, colours, and the language the booth should speak — there is no separate questions step. It returns a job id immediately; call check_generation, and do NOT describe the booth as designed or created until that says done. The result is a DRAFT with a draftId: nothing is in the operator's booth list until create_booth. Every call makes a new draft and spends 1 of its 3 full generations, and an account may start 10 drafts an hour — never call it speculatively or twice for one request; change a draft with refine_booth instead.

輸入參數prompt必填language

refine_booth

Refine a booth draft

Change a booth draft from start_booth, using the draftId check_generation returned. what='welcome' redraws the welcome screen from an instruction ('warmer colours', 'bigger headline', 'less clutter') while keeping the design; add orientation 'phone' or 'laptop' to redraw only that screen (1 redraw) — without it both screens are redrawn (2). what='app-background' redraws the calmer backdrop behind the rest of the booth (1 redraw). what='everything' rebuilds the whole draft from a NEW full description (spends 1 of the draft's 3 full generations) — only when the operator wants a different booth, not a tweak. A draft has 5 redraws in total; check_generation reports what is left. Title, headline, link name and colours cannot be edited directly: they change only through a redraw instruction, or at create time (title, slug). Returns a job id; call check_generation. Call only when the operator asks for a change — never iterate on your own.

輸入參數what必填draftId必填instruction必填orientation

create_booth

Create the booth

Create the booth from a finished draft — the step that makes something real, live at its public link. Call it only after the operator has seen the draft via check_generation and agreed to create it; the title and link name (slug) default to the draft's unless the operator chose others. It reads the draft first (so everything set with update_booth_draft — settings, frames, filters, AI effect — is carried), checks the link name, draws the booth's own three photo-strip frames (3 images, up to five minutes), adds three starter frames from the catalogue and the Studio's default 'Normal' filter the way dreambooth.app/new does, then creates the booth with the draft's welcome design, background, colour theme and capture mode. Frames saved with save_frame and filters made with create_filter on this connection are carried automatically; ids can also be passed. Tell the operator it takes 2-6 minutes. Returns a job id; check_generation reports progress and, when done, the booth's public link, id and a dashboard link. If the link name is taken it stops before drawing anything — ask for another and call again. Creating twice with different link names makes two booths. The booth is live (unlisted) at once; there is no tool that edits or deletes a booth — changes happen in the dashboard.

輸入參數slugtitledraftId必填frameIdsfilterIdscaptureModeaiEffectTitle

get_booth_draft

Read a booth draft

Read a booth draft by its draftId — the same summary check_generation gives for a finished design, plus everything the draft has been given since (settings, chosen frames, filters, AI effect). Use it when the job from start_booth is no longer tracked, to show the draft again before create_booth, or to confirm what update_booth_draft applied. Reads only; nothing is generated or created. A draft lives 7 days on the operator's account.

輸入參數draftId必填

update_booth_draft

Change a booth draft's settings

Change a booth draft without a redraw: its title, link name, welcome button text, colours, capture mode, language, which frames and filters it carries, its AI effect, and the page settings the dashboard editor offers (photo count, countdown, timeouts, GIF/recording, retake, checkout, payment, result). Use it after check_generation shows the draft and the operator asks for one of these; what it sets is applied when create_booth runs. It cannot change the welcome headline or subtext of an AI-designed welcome (those are painted into the image — use refine_booth), and prices or packages are set in the dashboard. Answers at once with the updated draft, `applied` (what landed) and `rejected` (what did not, and why) — relay a rejection as a sentence, never as success. It never touches a booth that already exists.

輸入參數slugtitledraftId必填palettesubtextframeIdsheadlinelanguagesettingsfilterIdsbuttonTextcaptureMode另有 1 個

版本歷史

1
  1. v0.1.0最新Sep 16, 2026

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