CONNECT APP
Build with RunPod
Artificial Intelligence (AI)
- API key
MCP
Give your agent RunPod tools
Every RunPod action is exposed as an MCP tool on Pipedream's remote server. Point a client at it with your end user's ID and Connect resolves that user's RunPod account for each tool call — you store no tokens.
// 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": "runpod",
},
},
},
)
const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)
const { tools } = await mcp.listTools()
// Every tool arrives with its own input schema — run one with mcp.callTool().# access_token: mint a short-lived token with the Connect SDK — see the MCP guide
headers = {
"Authorization": f"Bearer {access_token}",
"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": "runpod",
}
async with streamablehttp_client("https://remote.mcp.pipedream.net/v3", headers=headers) as (read, write, _):
async with ClientSession(read, write) as session:
await session.initialize()
tools = await session.list_tools()
# Every tool arrives with its own input schema — run one with call_tool().API PROXY
Call the RunPod API directly
For an endpoint with no pre-built tool, the Connect proxy forwards your request to the RunPod API with the connected user's credentials attached. You store no tokens and write no refresh logic.
const resp = await pd.proxy.get({
externalUserId: "{external_user_id}", // any stable ID for this user in your system
accountId: "apn_xxxxxxx",
url: "https://api.runpod.io/graphql",
})
// Any allowed RunPod endpoint works here. Pipedream attaches the
// connected account's credentials to the outgoing request.# The path segment is the target URL, URL-safe base64 encoded:
# https://api.runpod.io/graphql
curl "https://api.pipedream.com/v1/connect/{project_id}/proxy/aHR0cHM6Ly9hcGkucnVucG9kLmlvL2dyYXBocWw?external_user_id={external_user_id}&account_id=apn_xxxxxxx" \
-H "Authorization: Bearer {access_token}" \
-H "x-pd-environment: production"SDK
Run RunPod actions from your backend
Connect a user's RunPod account once, then discover and run its tools on their behalf from your own code — TypeScript, Python, or plain HTTP.
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 tools = await pd.components.list({
app: "runpod",
componentType: "action",
})from pipedream import Pipedream
pd = Pipedream(
client_id="{oauth_client_id}",
client_secret="{oauth_client_secret}",
project_id="{project_id}",
project_environment="production",
)
tools = pd.components.list(
app="runpod",
component_type="action",
)curl "https://api.pipedream.com/v1/connect/{project_id}/components?app=runpod&component_type=action" \
-H "X-PD-Environment: production" \
-H "Authorization: Bearer {access_token}"TOOLS
RunPod actions
On-demand operations your product or agent can configure and run on behalf of a connected user.
No RunPod actions are available yet.
No RunPod triggers are available yet.
MULTI-APP
Use RunPod with other popular apps
Most products don't stop at one integration. Pair RunPod with the other apps your users rely on, and ship use cases that span both.
- App slug
- runpod
- Authentication
- API key
- Categories
- Artificial Intelligence (AI)
- Actions
- 0
- Triggers
- 0
- API proxy
- Available