Google Gemini ACTION
Generate Content from Text
Generates content from text input using the Google Gemini API. See the documentation
- Action
- Writes data
- API key
- SDK
- MCP
IMPLEMENTATION
Call this tool
Connect a user's Google Gemini account once, then configure and run Generate Content from Text 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: "google_gemini-generate-content-from-text",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
google_gemini: { authProvisionId: "apn_xxxxxxx" },
model: "Model",
text: "Prompt Text",
},
})
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": "google_gemini-generate-content-from-text",
"configured_props": {
"google_gemini": { "authProvisionId": "apn_xxxxxxx" },
"model": "Model",
"text": "Prompt Text"
}
}'// 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": "google_gemini",
},
},
},
)
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: "google_gemini-generate-content-from-text",
arguments: {
model: "Model",
text: "Prompt Text",
},
})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 |
|---|---|---|
model Model | string | The model to use for content generation Required Dynamic |
text Prompt Text | string | The text to use as the prompt for content generation Required |
responseFormat JSON Output | boolean | Enable to receive responses in structured JSON format instead of plain text. Useful for automated processing, data extraction, or when you need to parse the response programmatically. You can optionally define a specific schema for the response structure. Optional |
history Conversation History | string[] | Previous messages in the conversation. Each item must be a valid JSON string with text and role (either user or model). Example: {"text": "Hello", "role": "user"} Optional |
safetySettings Safety Settings | string[] | Configure content filtering for different harm categories. Each item must be a valid JSON string with category (one of: HARASSMENT, HATE_SPEECH, SEXUALLY_EXPLICIT, DANGEROUS, CIVIC) and threshold (one of: BLOCK_NONE, BLOCK_ONLY_HIGH, BLOCK_MEDIUM_AND_ABOVE, BLOCK_LOW_AND_ABOVE). Example: {"category": "HARASSMENT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"} 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
- google_gemini-generate-content-from-text
- Version
- 0.2.2
- App
- Google Gemini
- Authentication
- API key
- Read-only
- No
- Destructive
- No
- Open world
- Yes
- Source
- View on GitHub ↗