Writer ACTION
Run Application
Run a saved no-code application (agent) with the inputs it expects and return the generated content. Discover the agent's
id with List Applications, then call Get Application to see the input field ids (names) it requires before running. Provide inputs as a JSON array of { id, value } objects, where each id is an input field name from the application's schema (not the application id) and value is an array of strings (one entry per value for that field). Example: call with applicationId="3f9c..." and inputs=[{ "id": "topic", "value": ["Velociraptor exhibit"] }, { "id": "tone", "value": ["exciting"] }] (here "topic" and "tone" are input field names) -> returns the agent's generated content. See the documentation- Action
- Writes data
- API key
- SDK
- MCP
IMPLEMENTATION
Call this tool
Connect a user's Writer account once, then configure and run Run Application 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: "writer-run-application",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
writer: { authProvisionId: "apn_xxxxxxx" },
applicationId: "Application ID",
inputs: "Inputs",
},
})
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": "writer-run-application",
"configured_props": {
"writer": { "authProvisionId": "apn_xxxxxxx" },
"applicationId": "Application ID",
"inputs": "Inputs"
}
}'// 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": "writer",
},
},
},
)
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: "writer-run-application",
arguments: {
applicationId: "Application ID",
inputs: "Inputs",
},
})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 |
|---|---|---|
applicationId Application ID | string | The UUID of a no-code application (agent). Discover ids with List Applications; inspect an agent's required input schema with Get Application before running it. Required |
inputs Inputs | string | JSON array of the agent's inputs. Each entry is { "id": <input field name>, "value": [<string>, ...] }, where id is an input field name from the application's schema (not the application id). Use Get Application to discover the valid input field ids. Example: [{ "id": "topic", "value": ["raptors"] }]. Required |
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
- writer-run-application
- Version
- 0.0.2
- App
- Writer
- Authentication
- API key
- Read-only
- No
- Destructive
- No
- Open world
- Yes
- Source
- View on GitHub ↗