Beehiiv ACTION
Get Post Analytics
Get aggregated analytics across all posts — open rates, click rates, unsubscribes, etc. Filter by audience (free/premium), platform (web/email), or content tags. Returns metrics: recipients, delivered, opens, unique_opens, open_rate, clicks, unique_clicks, click_rate, unsubscribes, spam_reports. Use List Posts to see individual post details. Use Get Publication Info to get the publication ID. See the documentation
- Action
- Read only
- API key
- SDK
- MCP
IMPLEMENTATION
Call this tool
Connect a user's Beehiiv account once, then configure and run Get Post Analytics 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: "beehiiv-get-post-analytics",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
beehiiv: { authProvisionId: "apn_xxxxxxx" },
publicationId: "Publication ID",
audience: "Audience",
},
})
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": "beehiiv-get-post-analytics",
"configured_props": {
"beehiiv": { "authProvisionId": "apn_xxxxxxx" },
"publicationId": "Publication ID",
"audience": "Audience"
}
}'// 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": "beehiiv",
},
},
},
)
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: "beehiiv-get-post-analytics",
arguments: {
publicationId: "Publication ID",
audience: "Audience",
},
})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 |
|---|---|---|
publicationId Publication ID | string | The publication ID. Use Get Publication Info to find this. Required |
audience Audience | string | Filter by audience. Options: free, premium, all. Optional |
platform Platform | string | Filter by platform. Options: web, email, both, all. Optional |
contentTags Content Tags | string[] | Filter analytics by content tags. 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
- beehiiv-get-post-analytics
- Version
- 0.0.2
- App
- Beehiiv
- Authentication
- API key
- Read-only
- Yes
- Destructive
- No
- Open world
- No
- Source
- View on GitHub ↗