CloudCrane workspace

ai.cloudcranev1.0.0更新於 Oct 4, 2026

Read and build a CloudCrane workspace: datasets, field contracts, review queue, receipts, runs.

已驗證Streamable HTTP可網頁執行Developer ToolsData & Analytics

概覽

AI 產生的概覽

讓助理讀取 CloudCrane 工作區中的資料集、欄位契約、審核佇列、回執與執行紀錄,並在獲准時協助建置與部署工具。

功能
透過 Streamable HTTP 將代理連接到 CloudCrane。每個連線都取得 17 個唯讀工具,例如 list_datasets、get_dataset、list_contracts、get_readiness、list_review_items、get_receipts、list_value_sets 與 get_run,以及用來檢視已部署內容、漂移警示、用量與審核的工具。被允許建置的連線還會取得 13 個寫入工具,包括 create_dataset、create_field、update_field、create_value_set、start_run、publish_release、request_approval、deploy_tool、update_tool、create_tool_key 與 run_scenarios。任何連線都不能越過準確率門檻發布、裁定審核項目、修改已儲存的值、扣留紀錄、刪除任何內容,或從安全欄位移除值。
適用情境
當你希望自己的代理檢視在 CloudCrane 中建置的內容,或在與儀表板相同的檢查下協助建置與部署資料工具時使用。另有獨立端點將一個已部署工具提供給終端使用者的代理。
執行需求
位於 cloudcrane.ai 的遠端 Streamable HTTP 端點,不需要本機執行環境。使用 CloudCrane 帳號透過 OAuth 登入,或以 Authorization Bearer 標頭送出建置金鑰。用戶端每次 POST 都必須送出 Accept: application/json, text/event-stream;只允許 POST。工作區端點會拒絕帶有 Origin 標頭的要求,因此需從伺服器或桌面用戶端呼叫。
安裝前請注意
工作區端點會開啟整個工作區,因此應把 OAuth 授權或建置金鑰視為敏感資訊,並在 Developers 下撤銷不再使用的應用程式。建置類工具會變更資料並帶有相應標記,用戶端可能在每次呼叫前詢問。除非擁有者開啟,匯入的紀錄內容會保持隱藏。已部署工具端點使用個別的工具金鑰。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 CloudCrane workspace,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。

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "workspace": {
      "type": "http",
      "url": "https://cloudcrane.ai/api/build/mcp"
    }
  }
}

README

CloudCrane MCP

[smithery badge] [CloudCrane workspace MCP connector – tool definition quality and endpoint health on Glama]

Connect your AI agent to CloudCrane over MCP.

In Claude: find CloudCrane in the connectors directory and connect.

CloudCrane turns a messy catalog into data an agent can be trusted with. Rules run before any model, the model may only answer from values you allowed, and every value carries a receipt saying how it was decided. Safety exclusions are enforced in the database query, so a record whose value is unknown is left out rather than assumed safe.

There are two MCP endpoints. Both speak Streamable HTTP (stateless, no SSE stream).

EndpointSigns in withWhat it opens
https://cloudcrane.ai/api/build/mcpYour CloudCrane account (OAuth), or a build key cc_build_…Your workspace, for your own agent while you build
https://cloudcrane.ai/api/mcp/<tool>A tool key cc_live_…One deployed tool, for your end users' agents

The workspace MCP

Let your own agent read what you are building and, if you allow it, help build it.

Connect with OAuth

In an MCP client that supports OAuth sign-in, add the URL with no key:

https://cloudcrane.ai/api/build/mcp

The client opens a CloudCrane page where a workspace owner picks the workspace and what the agent may do, then signs you in. Or install it from Smithery.

Tested with Claude, ChatGPT, Cursor, Cline and Smithery. Exact settings for each are in llms-install.md, which an agent can follow to set it up.

Claude: connect from the connectors directory, or Settings → Connectors → Add custom connector with the URL above, keeping Sign in now and Register automatically.

ChatGPT: add a custom MCP server with the URL above and choose OAuth.

Cursor (~/.cursor/mcp.json):

json
{ "mcpServers": { "cloudcrane": { "url": "https://cloudcrane.ai/api/build/mcp" } } }

Cline (cline_mcp_settings.json):

json
{ "mcpServers": { "cloudcrane": { "transport": { "type": "streamableHttp", "url": "https://cloudcrane.ai/api/build/mcp" } } } }

The page shows where it will send you back before anything else, because an app's name is only what it calls itself. It starts on read only. Each app you approve shows up in the dashboard under Developers, where you can revoke it.

Or with a build key

For a client without OAuth, an owner makes a build key under Developers and sends it as a header:

sh
claude mcp add --transport http cloudcrane https://cloudcrane.ai/api/build/mcp \  --header "Authorization: Bearer $CLOUDCRANE_BUILD_KEY"

What it can do

Every connection reads (17 tools): list_datasets, get_dataset, list_contracts, get_readiness, list_review_items, get_receipts, list_value_sets and get_run to find its way around; list_tools, list_scenarios, get_tool_insights, list_drift_alerts, get_usage and get_next_actions to watch what is deployed and what needs doing; list_approvals, get_approval and list_events to follow up. They run inside a read-only database transaction.

A connection allowed to build also gets 13: create_dataset, create_field, update_field, create_value_set, import_value_set_version, start_run, publish_release and request_approval to build; deploy_tool, update_tool, create_tool_key, create_scenario and run_scenarios to put it in front of users. Each goes through the same checks as the dashboard, is recorded as made by that connection, and is marked as changing data, so clients such as Claude ask you before each call.

What no connection can do: publish past the accuracy gate, decide a review item, edit a stored value, withhold a record, delete anything, or remove a value from a safety field. Those stay with a person, because a receipt names who decided.

Imported record contents stay hidden unless the owner turns them on. The workspace MCP is included in every CloudCrane plan, Free too.

Full reference: cloudcrane.ai/docs/build-mcp.

A deployed tool

Each tool you deploy is its own MCP server. Your agent sees search_<tool> and get_<tool>, plus find_values when the tool has value set fields. Their input schema is generated from your contracts, so the agent picks values from an enum of your list and cannot ask for one you never defined.

Claude Code

sh
claude mcp add --transport http catalog https://cloudcrane.ai/api/mcp/catalog \  --header "Authorization: Bearer $CLOUDCRANE_TOOL_KEY"

Claude Desktop, Cursor, Windsurf

json
{  "mcpServers": {    "catalog": {      "url": "https://cloudcrane.ai/api/mcp/catalog",      "headers": { "Authorization": "Bearer cc_live_..." }    }  }}

Some clients call the block servers instead of mcpServers, and some want "type": "http" next to the url.

  • n8n: MCP Client Tool node, transport HTTP Streamable, Bearer authentication.
  • LangChain: MultiServerMCPClient with transport streamable_http and a headers dict.
  • OpenAI Agents SDK: MCPServerStreamableHttp with the url and headers.

The same tool also answers plain REST at POST /api/v1/tools/<tool>/search. Full reference: cloudcrane.ai/docs/deploy.

Things that look like a broken server

  • 406: MCP requires Accept: application/json, text/event-stream on every POST, even though these endpoints never send a stream.
  • 405 on GET: the endpoints are stateless and offer no SSE stream, so only POST is allowed. A client that silently falls back to SSE connects but lists no tools.
  • 403 on the workspace MCP: it opens a whole workspace, so a request from a browser (any request with an Origin header) is refused. Call it from a server or a desktop client.

Links

This repository holds documentation and the registry entry (server.json), not the server's source.

來源:README.md,提交 b44f80a

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版本歷史

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  1. v1.0.0最新Oct 4, 2026