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 Knowledges 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.
Agents consume MCP servers directly through Agent Creator capabilities. This is the preferred way to expose DataGalaxy to an agent.
1
Create or open a workspace
From the Prisme.ai console, create a new workspace (or open the one that will host the connector).
2
Install the DataGalaxy app
Open the workspace Imports panel, search for DataGalaxy and install it.
3
Configure the credentials
Open the freshly installed app instance settings and fill in the required fields (see the Usage as App tab for the field-by-field reference).
4
Copy the MCP endpoint and API key
Still on the app instance configuration page, copy the values of MCP Endpoint and MCP API Key — both are generated automatically on install.
5
Open Agent Creator
Switch to Agent Creator and open the agent you want to extend.
6
Add a capability
Add a new capability to the agent:
If a dedicated DataGalaxy capability exists — select it and paste the MCP API Key into the mcp-api-key field. The server URL is already wired.
Otherwise — select the generic custom_mcp capability, paste the MCP Endpoint into the Server URL field, then open the Headers field and add an mcp-api-key entry whose value is the MCP API Key copied earlier:
{ "mcp-api-key": "your-mcp-api-key"}
7
Save
The agent now has access to every DataGalaxy tool exposed by the MCP server.
8
Brief the agent in its system prompt
Wiring the capability is not enough — the agent also needs to know the MCP exists and when to reach for it. Add a short paragraph to the agent’s system prompt. Copy-pasteable starter:
You have access to the DataGalaxy MCP server. Use it whenever the user asks about catalog content — sources, models, structures (tables, fields), glossary terms, links, comments or tasks. Examples: "Find all glossary terms tagged GDPR", "List the structures of the Snowflake source", "Add a comment to the customer table", "Create a task to review the orders dataset". Prefer calling MCP tools directly over guessing, and confirm with the user before any destructive action (delete a structure, remove a glossary term, close a task).
Refine the trigger keywords (source names, glossary domains, project tags) so the agent reliably picks up the right intent in your context.
Use this flow to plug the DataGalaxy MCP into an Knowledges 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 Knowledges 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.