Use this file to discover all available pages before exploring further.
The DataGalaxy app provides full read/write access to the DataGalaxy data catalog API. It can be used either as a Builder app (automations call DataGalaxy instructions directly) or as a remote MCP server consumed by an AI Knowledge agent.
Catalog Management
Sources, containers, structures, fields, glossary, usages, data processing
Links & Collaboration
Relationships, comments and tasks across any catalog entity
Dual Interface
Use as Builder app or MCP server exposed to agents
Base URL of the DataGalaxy API (default https://api.datagalaxy.com)
Authentication Token
PAT or integration token, stored as a workspace secret
MCP Endpoint
Auto-populated on install — URL of the MCP endpoint for this instance
MCP API Key
Auto-populated on install — signed key used in the mcp-api-key header. Do not modify
MCP Endpoint and MCP API Key are generated automatically by the onInstall flow and are only needed if you intend to expose this instance as an MCP server (see the next tab).
Every instruction resolves credentials from the workspace configuration via buildAppAuth. Unless stated otherwise, all IDs use DataGalaxy’s DoubleUuid format and versionId refers to a workspace version ID returned by listVersions.
- DataGalaxy.createLink: versionId: '{{versionId}}' fromId: '{{field.id}}' toId: '{{businessTermId}}' type: implements- DataGalaxy.createComment: versionId: '{{versionId}}' entityId: '{{field.id}}' content: <p>Linked to business term.</p>
The DataGalaxy app ships with a built-in MCP server. Each app instance gets its own signed mcp-api-key that encodes the workspace ID and a credentials lookup URL, so no DataGalaxy token is ever passed through headers — credentials are resolved server-side from the app configuration.
Use this flow to plug the DataGalaxy MCP into an AI Knowledge agent that does not yet support the native MCP picker.
1
Install the DataGalaxy app
Install and configure the app in the same workspace as your agent (see the Usage as App tab). Once configured, mcpEndpoint and mcpApiKey are auto-populated.
2
Copy the MCP credentials
Open the app instance config and copy the values of MCP Endpoint and MCP API Key.
3
Open your AI Knowledge project
Navigate to Advanced > Tools.
4
Add an MCP tool
Click Add and select the MCP tab.
5
Fill in the endpoint
Paste the MCP Endpoint URL copied from the app instance.
6
Add the auth header
In the Headers field, add the signed API key:
{ "mcp-api-key": "your-mcp-api-key"}
7
Save
The agent can now list and call DataGalaxy tools through the MCP endpoint.
The signed mcp-api-key encodes the workspace ID and the getConfig webhook URL. The MCP server validates the signature using the central app secret and transparently fetches the DataGalaxy accessToken and baseUrl from the installed app. Credentials are cached per tenant for 10 minutes.
See the Usage as App tab for the full argument list and enum values shared by create/update tools across sources, containers, structures, fields, properties, usages and data processing.
“Not configured” — No credentials could be resolved. Either complete the app install with a valid token, pass an Authorization: Bearer header, or call configureDataGalaxy before the first tool call.“Invalid API key” — The mcp-api-key header does not match the central app secret. Reinstall the app instance to regenerate a signed key.“Credentials lookup failed” — The MCP endpoint could not reach the getConfig webhook of the installed app. Verify that the app instance is still installed in the expected workspace.