
ApparelHub
io.github.ApparelHub-AIv0.15.2更新於 Sep 29, 2026
Run a custom-merch store from an agent: design, build products, list on every channel, fulfill.
概覽
讓助理端到端經營 ApparelHub 客製周邊商店:設計服飾、建立並上架商品、處理訂單與履約。
- 功能
- 提供 121 個工作流程層級的工具,包裝 ApparelHub Agent API,涵蓋商店初始化與通路連接、目錄瀏覽、服飾設計與圖片品質檢查、商品建立與通路刊登、訂單生命週期與履約問題、分析、選集,以及工作區與團隊管理。ship_product 等高階工具會依正確順序串接變體解析、樣機圖產生、商品建立與通路同步,另有 api_request 逃生通道可呼叫任何 agent API 端點。讀取類工具為唯讀;商品與設計類工具預設存為草稿而非直接上線,系統級操作類變更預設先試跑。
- 適用情境
- 適合讓助理端到端經營客製周邊商店——設計並上架服飾、同步到履約與銷售通路、處理新進訂單——而不只是回答相關問題。也適合希望在各種支援 MCP 的用戶端使用型別化工具,而非 markdown 技能或 recipes 的商家。
- 執行需求
- 兩種方式:使用託管遠端端點 mcp.apparelhub.ai,透過 OAuth 2.1 授權(使用者無需處理 API 金鑰);或在本機以 stdio 執行 npm 套件 @apparelhub/mcp-server,需要 Node.js 20+、ApparelHub 帳號,並以環境變數 APPARELHUB_API_KEY 提供 API 金鑰。本機的設計與品質工具另需 Python 3 與 Pillow,OCR 可選裝 tesseract;託管連接器不需要這些。選用變數:APPARELHUB_MCP_TELEMETRY、APPARELHUB_MCP_PYTHON。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 ApparelHub,將其新增到工作區。
- 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。
其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"apparelhub-mcp": {
"type": "http",
"url": "https://mcp.apparelhub.ai"
}
}
}README
@apparelhub/mcp-server
Workflow-level MCP tools that let an AI agent run an ApparelHub store end to end: set it up, design apparel, build products, list them across sales channels, and work the orders and listings that come back. Each tool wraps the ApparelHub Agent API and bakes in the platform's hard-won production lessons, so the agent gets correct behavior for free instead of learning the gotchas itself.
There are two ways to run it: a hosted connector you authorize with OAuth (recommended, no API key to handle) and this npm package you run yourself with a key. Both serve the identical tool surface.
Status: early access. The npm package is pre-1.0 while the surface stabilizes. The agent-facing tool surface is v1 and is the contract we keep stable (see
CHANGELOG.mdand Versioning).
What makes this different
A thin wrapper around a REST API just renames HTTP calls. These tools are at the workflow
level: one ship_product call resolves variants, generates and waits for a mockup (through the
waiting until its images are actually published), creates the product with the right field names,
adds every variant,
associates it with a store, and syncs to fulfillment and channels in the correct order, refusing a
negative-margin price and warning on known variant traps along the way. The scar tissue lives in
the code, not in your agent's context.
Connect
Prefer the hosted connector. Authorizing it provisions the API key for you, so there is no credential to create, paste, rotate, or leak into a config file. Reach for the self-run package only when your client cannot speak remote MCP or OAuth, or when you specifically want the server running on your own machine.
Recommended: the hosted connector
Add that URL to any MCP client that supports remote servers, sign in to ApparelHub, and approve. You never handle an API key. Approving the grant provisions a connector key on your account (or reuses the one you already have), and the hosted server resolves your session to it on every call. Nothing to paste, nothing to rotate by hand, nothing sitting in a dotfile.
The hosted server also carries the imaging toolchain the design and quality tools need, so transparency keying, image statistics, and OCR all work with no local dependencies at all: no Node, no Python, no Pillow, no tesseract.
Claude Code
Then run /mcp and choose Authenticate.
Any client that reads an MCP config file
claude.ai — add it as a custom connector under Settings → Connectors, paste the same URL, then authorize when prompted.
The bare origin above is the server's canonical address: it is the resource identifier its own
OAuth metadata advertises. A path is not routed on, so an existing config pointing at
https://mcp.apparelhub.ai/mcp keeps working and needs no change.
What the handshake actually does
Standard OAuth 2.1, nothing custom for you to configure. Your client discovers the authorization
server from /.well-known/oauth-protected-resource (RFC 9728), registers itself dynamically, and
runs an authorization-code flow with PKCE (S256) for the mcp scope against
https://api.apparelhub.ai. Refresh tokens and revocation are supported. Access tokens are opaque:
the hosted server exchanges yours for your connector key server-side, so the key is never in your
client, your config, or your chat history.
Key slots and revoking
One connector key is minted per account and shared across every chat surface you grant, and it counts against your plan's API key allowance. The Free plan includes API access with one slot, so if that slot is already taken by a self-service key the consent screen says so and offers to free it or upgrade. To revoke, disconnect from the client that holds the grant, or delete the connector key at https://apparelhub.ai/developer/api-keys.
Alternative: run the package yourself
Requirements:
- Node.js 20+.
- An ApparelHub account and API key — generate one at https://apparelhub.ai/developer/api-keys.
- For the design + quality tools only: Python 3 with Pillow (transparency keying, image QC) and optionally tesseract (OCR text detection). These run locally; if they're missing, those tools return a clear notice telling you exactly what to install, and never crash.
The server reads your key from the APPARELHUB_API_KEY environment variable at startup and speaks
MCP over stdio. It never accepts the key as a tool argument, and the API host is pinned (no
override).
Claude Code
Cursor
Aider
Any other MCP client
Same shape everywhere: run npx -y @apparelhub/mcp-server with APPARELHUB_API_KEY in its
environment.
Environment variables
Tools
121 tools. docs/TOOLS.md walks through the core groups; call tools/list from
your agent for the authoritative live schemas.
- Setup & connect —
check_setup_readiness(what the account has, what it needs, the single next action),list_connectable_providers,connect_fulfillment_providerandconnect_sales_channel(API-token providers connected entirely in chat), plusstart_channel_connect/check_connection_statusfor the browser-based ones (Printful, Shopify, TikTok Shop, Fourthwall). - Read —
list_my_workspaces,list_my_stores,list_my_designs,list_my_products,list_my_orders,get_order_details. - Catalog —
browse_catalog,get_garment_details,find_garments(search every connected provider at once for a capability),recommend_garment,list_catalog_providers. - Design —
design_apparel,iterate_design,upload_design(bring artwork the merchant already owns),fit_aspect(quota-free reshape), design lifecycle (archive_design,restore_design,delete_design), and split primitivesgenerate_image,process_transparency,verify_design_text. - Product —
ship_product,update_product,delete_product,unsync_from_channel,diagnose_tiktok_listings, and split primitivescreate_product,add_variants,sync_to_fulfillment,sync_to_channel. - Orders — lifecycle (
approve_order,unapprove_order,hold_order,cancel_order,confirm_order,submit_order_to_fulfillment,check_order_status,reconcile_order), draft edits (add_order_item,remove_order_item), and design-approval holds (list_order_holds,approve_order_hold,request_hold_changes). - Fulfillment issues —
report_fulfillment_issue(report a defect on an order),list_fulfillment_issues(per-order or workspace-wide inbox),check_fulfillment_issue(full issue plus the provider-ready problem report),resolve_fulfillment_issue(record the provider filing, close with a resolution, or create a replacement order). - Channel intelligence — what the sales channel itself reports and what you can set on it:
channel_performance,channel_opportunities,channel_coverage,listing_changes(did the last edit actually work),describe_listing_attributes,set_listing_attributes,set_channel_settings,import_size_measurements. - Analytics —
analytics_summary,analytics_timeseries,analytics_breakdown,analytics_ops,analytics_portfolio. - Collections —
list_collections,get_collection,create_collection,update_collection,delete_collection,add_products_to_collection,remove_product_from_collection,sync_collection. - Cross-workspace transfer —
copy_product_to_workspace,move_product_to_workspace,check_product_move, and the design equivalents. - Workspace & team management (agency / Enterprise, account-wide key) — workspaces
(
create_workspace,update_workspace,delete_workspace,check_workspace_deletion,assign_workspace_member,unassign_workspace_member,move_store_to_workspace,get_role_matrix) and team (get_account_overview,list_account_members,remove_member,invite_member,list_invites,revoke_invite,resend_invite,accept_invite). - Store & order management — store settings/lifecycle (
get_store_settings,update_store_settings,create_store,archive_store,unarchive_store,activate_store), order payment/ops (record_order_payment,mark_order_no_payment,set_order_payment_method,sync_orders,estimate_order_costs,get_orders_summary,list_pending_fulfillments), andarchive_product/restore_product. - Systems of action —
analyze_what_works,auto_optimize_listings,cascade_price_change,set_prices_by_margin,recover_from_outage. - Safety —
verify_design_quality,verify_mockup_quality,check_design_compliance. - API escape hatch —
get_api_reference(discover the full agent API from the live OpenAPI spec) andapi_request(call any/agents/v1endpoint when no dedicated tool fits).
Read tools are read-only. Product and design tools default to draft, never live, enforce
pricing floors, and guard known variant traps. Systems-of-action mutations default to a dry run
and only take safe actions (archive, never delete) when applied. Every product/order/store result
carries a view_url back into apparelhub.ai. Errors come back in a consistent shape
({error: {code, message, retry_after?, suggestion?}}) — tools never throw across the MCP boundary.
get_api_reference also reports what the server you are actually talking to serves — its version,
tool count, and every tool name — so an agent can tell "that tool does not exist" apart from "my
cached tool list is stale" instead of guessing.
Privacy
An optional, coarse usage signal helps improve the tools. It sends only non-identifying
features — the tool name, outcome, latency, error code, and a strict allowlist of coarse fields
(e.g. AI source name, garment category). It never sends prompts, images, ids, URLs, or customer
data. It's buffered and fire-and-forget (it can never affect a tool call). Turn it off entirely
with APPARELHUB_MCP_TELEMETRY=off.
The hosted connector additionally records one operational metric per request (outcome, latency, and for a tool call the tool name). It carries no per-identity dimension and no user data.
Skill vs. MCP vs. recipes
ApparelHub ships the agent surface in three forms:
- The markdown skill is the lowest-friction way to use ApparelHub from Claude Code — it teaches the agent the REST API and the design rules directly.
- This MCP server turns that knowledge into a typed, callable tool surface (with the systems-of-action tools) that works across any MCP-capable agent, and, through the hosted connector, in chat surfaces that cannot run a skill or a local process at all.
- The recipes are end-to-end operating blueprints you drop into your agent's runtime: a charter the agent follows, a memory model it keeps across runs, and the prompts to start it. They drive this tool surface, with money and go-live gates on by default.
Use the skill for a quick start in Claude Code; use the MCP server when you want typed tools, the higher-order workflows, or a client other than Claude Code; use a recipe when you want the agent to run a whole store pattern rather than answer one request at a time.
Development
The image tools shell out to bundled Python scripts in python/; the imaging layer is
injectable, so the tool orchestration is unit-tested with a fake and the scripts are smoke-tested
directly.
Versioning & stability
The tool surface is versioned separately from the package (this is v1). When the underlying
REST API evolves, the server adapts internally — the agent-facing tool names + shapes stay stable.
That's the contract that lets you install once and keep working. Package releases follow
Semantic Versioning; see docs/RELEASING.md.
On the hosted connector you are always on the current version, which is another reason to prefer
it: new tools appear without you upgrading anything. Clients cache the tool list, so ask
get_api_reference if you suspect yours has fallen behind.
License
MIT © ApparelHub. See LICENSE.
來源:README.md,提交 690daab
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1- v0.15.2最新Sep 29, 2026