Build with DigitalOcean Gradient™ AI Serverless Inference

// 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": "digitalocean_gradient_ai_serverless_inference",
      },
    },
  },
)

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": "digitalocean_gradient_ai_serverless_inference",
}

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().

const resp = await pd.proxy.get({
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  accountId: "apn_xxxxxxx",
  url: "https://inference.do-ai.run/v1/models",
})

// Any allowed DigitalOcean Gradient™ AI Serverless Inference 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://inference.do-ai.run/v1/models

curl "https://api.pipedream.com/v1/connect/{project_id}/proxy/aHR0cHM6Ly9pbmZlcmVuY2UuZG8tYWkucnVuL3YxL21vZGVscw?external_user_id={external_user_id}&account_id=apn_xxxxxxx" \
  -H "Authorization: Bearer {access_token}" \
  -H "x-pd-environment: production"

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: "digitalocean_gradient_ai_serverless_inference",
  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="digitalocean_gradient_ai_serverless_inference",
    component_type="action",
)

curl "https://api.pipedream.com/v1/connect/{project_id}/components?app=digitalocean_gradient_ai_serverless_inference&component_type=action" \
  -H "X-PD-Environment: production" \
  -H "Authorization: Bearer {access_token}"