Microsoft Power BI ACTION
List Datasets
List Power BI datasets (semantic models) in a workspace. Defaults to the authenticated user's personal My workspace when no workspace is specified. Pass
workspaceId (preferred, from List Workspaces) OR workspaceName to scope to a specific workspace. Each dataset includes id, name, webUrl, addRowsAPIEnabled (true for Push Datasets), isRefreshable, and defaultMode (Push, Streaming, PushStreaming, AsOnPrem, AsAzure). Use this tool to resolve a dataset name → ID before calling Refresh Dataset, Execute DAX Query, Get Refresh History, or Add Rows To Push Dataset. For push-dataset row inserts, call the dataset's GET tables endpoint (not exposed as a separate tool) by inspecting the dataset's name → tables are defined at dataset creation; the table name is the string configured at creation time (e.g., Species). See the documentation- Action
- Read only
- OAuth
- SDK
- MCP
IMPLEMENTATION
Call this tool
Connect a user's Microsoft Power BI account once, then configure and run List Datasets from your backend or agent.
import { PipedreamClient } from "@pipedream/sdk"
const pd = new PipedreamClient({
projectId: process.env.PIPEDREAM_PROJECT_ID!,
clientId: process.env.PIPEDREAM_CLIENT_ID!,
clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
projectEnvironment: "production",
})
const result = await pd.actions.run({
id: "microsoft_power_bi-list-datasets",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
microsoft_power_bi: { authProvisionId: "apn_xxxxxxx" },
workspaceId: "Workspace ID",
workspaceName: "Workspace Name",
},
})
console.log(result)curl -X POST https://api.pipedream.com/v1/connect/{project_id}/actions/run \
-H "Content-Type: application/json" \
-H "X-PD-Environment: production" \
-H "Authorization: Bearer {access_token}" \
-d '{
"external_user_id": "{external_user_id}",
"id": "microsoft_power_bi-list-datasets",
"configured_props": {
"microsoft_power_bi": { "authProvisionId": "apn_xxxxxxx" },
"workspaceId": "Workspace ID",
"workspaceName": "Workspace Name"
}
}'// accessToken: mint a short-lived token with the Connect SDK — see the MCP guide
const transport = new StreamableHTTPClientTransport(
new URL("https://remote.mcp.pipedream.net/v3"),
{
requestInit: {
headers: {
Authorization: `Bearer ${accessToken}`,
"x-pd-project-id": "{project_id}",
"x-pd-environment": "production",
"x-pd-external-user-id": "{external_user_id}", // any stable ID for this user in your system
"x-pd-app-slug": "microsoft_power_bi",
},
},
},
)
const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)
const { tools } = await mcp.listTools()
// listTools() hands your model this tool's input schema, so it can
// fill the arguments itself:
const result = await mcp.callTool({
name: "microsoft_power_bi-list-datasets",
arguments: {
workspaceId: "Workspace ID",
workspaceName: "Workspace Name",
},
})SCHEMA
Inputs
Pipedream supplies the connected account. Your application provides the operation-specific values below. Dynamic inputs are resolved against that user's account.
| Property | Type | Description |
|---|---|---|
workspaceId Workspace ID | string | ID of the workspace. Use the List Workspaces tool to see accessible workspaces. Omit to target My workspace. Optional |
workspaceName Workspace Name | string | Name of the workspace (alternative to Workspace ID). Use the List Workspaces tool to see accessible workspaces. Optional |
REFERENCE
Tool details
Behavior hints are published with the component in the Pipedream registry and surface as MCP tool annotations, so an agent can reason about a tool before it calls it.
- Registry key
- microsoft_power_bi-list-datasets
- Version
- 0.0.3
- App
- Microsoft Power BI
- Authentication
- OAuth
- Read-only
- Yes
- Destructive
- No
- Open world
- Yes
- Source
- View on GitHub ↗