CloudCrane MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@CloudCrane MCPlist my datasets, check catalog readiness, and show latest run receipts"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
CloudCrane MCP
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).
Endpoint | Signs in with | What it opens |
| Your CloudCrane account (OAuth), or a build key | Your workspace, for your own agent while you build |
| A tool key | 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/mcpThe 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):
{ "mcpServers": { "cloudcrane": { "url": "https://cloudcrane.ai/api/build/mcp" } } }Cline (cline_mcp_settings.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:
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.
Related MCP server: Nexxupp MCP Server
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:
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
Playground: the pipeline in your browser, no sign-up
This repository holds documentation and the registry entry (server.json), not
the server's source.
This server cannot be deployed
Maintenance
Related MCP Connectors
Context and control for any AI. Agent identity, scoped access, and proof across tools.
Verified, pay-per-use API tools for AI agents through one authenticated connection.
Build, validate, deploy — HTTP APIs, cron jobs, webhooks and MCP tools — from your AI client.
Supervised API-write gateway for AI agents with policy, human approval and execution receipts.
Related MCP Servers
AlicenseNot gradedqualityCmaintenanceEnables AI agents to execute provider tools through a self-hostable gateway with scoped keys, permissions, and accounting reservations.Apache 2.0
Nexxupp MCP Serverofficial
AlicenseBqualityCmaintenanceEnables AI agents to store and search private memory, explore and edit workspace stations, databases, tasks, and charts, and schedule calendar events through natural language. Supports local stdio and hosted HTTP modes with per-user OAuth scoping of tools.22MIT- FlicenseNot gradedqualityAmaintenanceGives AI agents access to a persistent document workspace so they can search, read, and update knowledge through 22 focused tools, 2 prompts, and 3 resources, with batch actions and direct workspace-item inspection. Runs either as a hosted Streamable HTTP endpoint with OAuth or API keys, or as a self-hosted stdio bridge pointed at your own instance.-
- AlicenseNot gradedqualityAmaintenanceGives AI agents and MCP-speaking clients such as Claude, Cursor, VS Code and Cline read/write access to a workspace through a single token, so they can create pages, query databases, append blocks, apply templates, comment, and upload files in plain language. It runs headless for CI, cron jobs and self-hosted deployments, keeping tool schemas and responses lightweight, with batched mutations, idempotency keys and retry handling built in.2,210 npmMIT