MULTI-APP TOOLKIT
Build with Google Gemini + Hugging Face
- Multi-app
- One MCP session
- 9 actions
- 0 triggers
- Managed auth
MCP
One MCP session, both toolsets
One session gives your product or agent every Google Gemini and Hugging Face tool at once — connect once, list tools, and call them like any single-app session.
// 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,hugging_face",
},
},
},
)
const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)
const { tools } = await mcp.listTools()
// One list, both toolsets: Google Gemini and Hugging Face tools arrive
// together, each keyed by its own app's slug.
// e.g. run Generate Content from Text:
const result = await mcp.callTool({
name: "google_gemini-generate-content-from-text",
arguments: {
model: "Model",
text: "Prompt Text",
},
})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 externalUserId = "{external_user_id}" // any stable ID for this user in your system
const [googleGeminiTools, huggingFaceTools] =
await Promise.all([
pd.components.list({ app: "google_gemini" }),
pd.components.list({ app: "hugging_face" }),
])
// One external user owns both connected accounts, so either app's tools
// run on their behalf with the same externalUserId.curl "https://api.pipedream.com/v1/connect/{project_id}/components?app=google_gemini" \
-H "X-PD-Environment: production" \
-H "Authorization: Bearer {access_token}"
curl "https://api.pipedream.com/v1/connect/{project_id}/components?app=hugging_face" \
-H "X-PD-Environment: production" \
-H "Authorization: Bearer {access_token}"
# Connect both accounts to the same external_user_id, then
# configure and invoke either app's tools on that user's behalf.ARCHITECTURE
One user, two connected accounts
Your user connects each account once, under whatever ID they already have in your product. The two stay independent — either can be revoked on its own — and your code reaches both through that one user.
Your product
external_user_id
{external_user_id}Pipedream Connect
Managed identity
Auth · tools · routing
Google Gemini
Connected account
Hugging Face
Connected account
TOOLS
Google Gemini tools
The Google Gemini tools this pairing puts in reach, each one running on your user's own connected account.
Actions
-
Generate Content from Text
actionGenerates content from text input using the Google Gemini API. See the documentationWritev0.2.2 -
Generate Content from Text and Image
actionGenerates content from both text and image input using the Gemini API. See the documentationWritev1.0.3 -
Generate Embeddings
actionGenerate embeddings from text input using Google Gemini. See the documentationWritev0.0.2
Triggers
No Google Gemini triggers are available yet.
TOOLS
Hugging Face tools
The Hugging Face tools this pairing puts in reach, each one running on your user's own connected account.
Actions
-
Document Question Answering
actionWant to have a nice know-it-all bot that can answer any question?. This action allows you to ask a question and get an answer from a trained model. See the docs.Read-onlyv0.0.2 -
Image Classification
actionThis task reads some image input and outputs the likelihood of classes. This action allows you to classify images into categories. See the docs.Read-onlyv0.0.2 -
Language Translation
actionThis task is well known to translate text from one language to another. See the docs.Read-onlyv0.0.2 -
Object Detection
actionThis task reads some image input and outputs the likelihood of classes and bounding boxes of detected objects. See the docs.Writev0.0.2 -
Text Classification
actionUsually used for sentiment-analysis this will output the likelihood of classes of an input. This action allows you to classify text into categories. See the docs.Writev0.0.2 -
Text Summarization
actionThis task is well known to summarize longer text into shorter text. Be careful, some models have a maximum length of input. That means that the summary cannot handle full books for instance. Be careful when choosing your model. See the docs.Read-onlyv0.0.2
Triggers
No Hugging Face triggers are available yet.
MULTI-APP
Works with more apps
The combinations customers connect alongside these two — nothing here is limited to a pair.
REFERENCE
Toolkit details
- x-pd-app-slug
- google_gemini,hugging_face
- Primary app
- Google Gemini (google_gemini)
- Second app
- Hugging Face (hugging_face)
- Authentication
- API key + API key
- Available actions
- 9
- Available triggers
- 0