Mindbody ACTION
List Staff
Returns staff members at the studio, including their IDs, names, bio, and role assignments (e.g., ClassTeacher, AppointmentInstructor). Use this to discover
staffId values needed by Book Appointment and Get Classes. Filter by filters to find staff with a specific role (e.g., AppointmentInstructor). See the documentation- Action
- Read only
- OAuth
- SDK
- MCP
IMPLEMENTATION
Call this tool
Connect a user's Mindbody account once, then configure and run List Staff 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: "mindbody-list-staff",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
mindbody: { authProvisionId: "apn_xxxxxxx" },
filters: "Role Filters",
locationId: 10,
},
})
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": "mindbody-list-staff",
"configured_props": {
"mindbody": { "authProvisionId": "apn_xxxxxxx" },
"filters": "Role Filters",
"locationId": 10
}
}'// 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": "mindbody",
},
},
},
)
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: "mindbody-list-staff",
arguments: {
filters: "Role Filters",
locationId: 10,
},
})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 |
|---|---|---|
filters Role Filters | string | Comma-separated list of role filters to narrow results. Valid values: ClassTeacher, AppointmentInstructor, Male, Female. Example: AppointmentInstructor. Optional |
locationId Location ID | integer | The ID of the location (studio). Use Get Site Info to discover valid location IDs. Optional |
limit Limit | integer | Maximum number of results to return per page. Minimum 1, maximum 200. Defaults to 100. Optional |
offset Offset | integer | Number of results to skip for pagination. Defaults to 0. 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
- mindbody-list-staff
- Version
- 0.0.3
- App
- Mindbody
- Authentication
- OAuth
- Read-only
- Yes
- Destructive
- No
- Open world
- Yes
- Source
- View on GitHub ↗