
CloudCrane workspace
ai.cloudcranev1.0.0更新于 Oct 4, 2026
Read and build a CloudCrane workspace: datasets, field contracts, review queue, receipts, runs.
概览
让助手读取 CloudCrane 工作区中的数据集、字段契约、审核队列、回执和运行记录,并在获准时协助构建和部署工具。
- 功能
- 通过 Streamable HTTP 将智能体连接到 CloudCrane。每个连接都获得 17 个只读工具,例如 list_datasets、get_dataset、list_contracts、get_readiness、list_review_items、get_receipts、list_value_sets 和 get_run,以及用于查看已部署内容、漂移告警、用量和审批的工具。被允许构建的连接还会获得 13 个写入工具,包括 create_dataset、create_field、update_field、create_value_set、start_run、publish_release、request_approval、deploy_tool、update_tool、create_tool_key 和 run_scenarios。任何连接都不能越过准确率门槛发布、裁定审核项、修改已存储的值、扣留记录、删除任何内容,或从安全字段中移除值。
- 适用场景
- 当你希望自己的智能体查看在 CloudCrane 中构建的内容,或在与仪表盘相同的检查下协助构建和部署数据工具时使用。另有独立端点将一个已部署工具提供给最终用户的智能体。
- 运行要求
- 位于 cloudcrane.ai 的远程 Streamable HTTP 端点,无需本地运行时。使用 CloudCrane 账户通过 OAuth 登录,或以 Authorization Bearer 请求头发送构建密钥。客户端每次 POST 都必须发送 Accept: application/json, text/event-stream;只允许 POST。工作区端点会拒绝带 Origin 请求头的请求,因此需从服务器或桌面客户端调用。
安装
在 SourceWeft 中
- 打开 控制台中的 CloudCrane workspace,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
其他 MCP 客户端
把它添加到你客户端的 mcpServers 配置中。
{
"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).
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:
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):
Cline (cline_mcp_settings.json):
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:
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
Claude Desktop, Cursor, Windsurf
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:
MultiServerMCPClientwith transportstreamable_httpand a headers dict. - OpenAI Agents SDK:
MCPServerStreamableHttpwith 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-streamon 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
Originheader) is refused. Call it from a server or a desktop client.
Links
- Docs
- Playground: the pipeline in your browser, no sign-up
- Integrations
This repository holds documentation and the registry entry (server.json), not
the server's source.
来源:README.md,提交 b44f80a
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0版本历史
1- v1.0.0最新Oct 4, 2026

