CloudCrane MCP

MCP serverDatabases & data

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

Use CloudCrane MCP in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add CloudCrane MCP and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use CloudCrane MCP

Details

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

CloudCrane MCPStart free

Install CloudCrane MCP

The server’s own address, for the clients that take one directly. Or connect ahel once and every client you use reads it from one address, with the account kept on ahel rather than in each client’s config.

  • Claude Code

    claude mcp add --transport http --scope user cloudcrane-mcp 'https://cloudcrane.ai/api/build/mcp'

    Run it once in your project, then open /mcp to approve any sign-in the server asks for.

  • Claude Desktop

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

    Add a custom connector in Settings, paste this address, and approve the sign-in.

  • Cursor

    cursor://anysphere.cursor-deeplink/mcp/install?name=cloudcrane-mcp&config=eyJ1cmwiOiJodHRwczovL2Nsb3VkY3JhbmUuYWkvYXBpL2J1aWxkL21jcCJ9

    Open the link and Cursor adds the server at that address.

  • ChatGPT

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

    In Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.

  • Codex

    codex mcp add cloudcrane-mcp --url 'https://cloudcrane.ai/api/build/mcp'

    Run it once, then sign in with codex mcp login cloudcrane-mcp if the server asks for an account.

From the project's README

As published by cloudcrane-dev/cloudcrane-mcp in README.md.

Connect your AI agent to CloudCrane over MCP.

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.

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:

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: list_datasets, get_dataset, list_contracts, get_readiness, list_review_items, get_receipts, list_value_sets, get_run. They run inside a read-only database transaction.

A connection allowed to build also gets: create_dataset, create_field, update_field, create_value_set, import_value_set_version, start_run, publish_release. Each goes through the same checks as the dashboard and is recorded as made by that connection.

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 comes with the Team plan.

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

Claude Desktop, Cursor, Windsurf

{
  "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.
  • 402 on the workspace MCP: the workspace isn't on a plan that includes it.

Links

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

Signals

Last commit
Oct 2026
Advanced
Delivery
workspace MCP server → your ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
ai-cloudcrane-workspace
Source
github.com/cloudcrane-dev/cloudcrane-mcp
Hosted endpoint
https://cloudcrane.ai/api/build/mcp