Peakon Employee Voice ACTION
List Segments
Lists all demographic and organizational segments configured in Peakon. Each segment includes a
contextId that can be passed to Get Engagement Overview and Get Driver Scores to scope analytics to a specific population (e.g. a department, region, or tenure band). Call this first whenever the user asks about a specific team, department, or demographic group and needs analytics scoped to it. See the Peakon API documentation- Action
- Read only
- OAuth
- SDK
- MCP
IMPLEMENTATION
Call this tool
Connect a user's Peakon Employee Voice account once, then configure and run List Segments 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: "peakon_employee_voice-list-segments",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
peakon_employee_voice: { authProvisionId: "apn_xxxxxxx" },
filterAttributeId: 10,
filterDirect: true,
},
})
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": "peakon_employee_voice-list-segments",
"configured_props": {
"peakon_employee_voice": { "authProvisionId": "apn_xxxxxxx" },
"filterAttributeId": 10,
"filterDirect": true
}
}'// 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": "peakon_employee_voice",
},
},
},
)
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: "peakon_employee_voice-list-segments",
arguments: {
filterAttributeId: 10,
filterDirect: true,
},
})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 |
|---|---|---|
filterAttributeId Filter by Attribute ID | integer | The ID of the attribute that is the source of a segment. Optional |
filterDirect Filter Direct Reports Only | boolean | When true, returns segments including only direct reports. When false, includes all reports. Optional |
filterManagerId Filter by Manager ID | integer | The employee ID of a manager to filter segments by. Use List Employees to find the ID. Optional |
filterType Filter by Type | string | The type of attribute that is the source of a segment. 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
- peakon_employee_voice-list-segments
- Version
- 0.0.2
- App
- Peakon Employee Voice
- Authentication
- OAuth
- Read-only
- Yes
- Destructive
- No
- Open world
- Yes
- Source
- View on GitHub ↗