CONNECT APP

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Artificial Intelligence (AI)

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MCP

Give your agent xAI tools

Every xAI 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 xAI account for each tool call — you store no tokens.

Pipedream Connect

// 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": "x_ai",
      },
    },
  },
)

const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)

const { tools } = await mcp.listTools()

// e.g. run Create Embedding:
const result = await mcp.callTool({
  name: "x_ai-create-embeddings",
  arguments: {
    embeddingModel: "Embedding Models",
    input: ["Input"],
  },
})

# 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": "x_ai",
}

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()

        # e.g. run Create Embedding:
        result = await session.call_tool("x_ai-create-embeddings", {
            "embeddingModel": "Embedding Models",
            "input": ["Input"],
        })

MCP guide →

API PROXY

Call the xAI API directly

For an endpoint with no pre-built tool, the Connect proxy forwards your request to the xAI API with the connected user's credentials attached. You store no tokens and write no refresh logic.

Pipedream Connect

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.x.ai/v1/models",
})

// Any allowed xAI 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.x.ai/v1/models

curl "https://api.pipedream.com/v1/connect/{project_id}/proxy/aHR0cHM6Ly9hcGkueC5haS92MS9tb2RlbHM?external_user_id={external_user_id}&account_id=apn_xxxxxxx" \
  -H "Authorization: Bearer {access_token}" \
  -H "x-pd-environment: production"

API proxy guide →

SDK

Run xAI actions from your backend

Connect a user's xAI account once, then run Create Embedding on their behalf from your own code — TypeScript, Python, or plain HTTP.

Pipedream Connect

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: "x_ai-create-embeddings",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    x_ai: { authProvisionId: "apn_xxxxxxx" },
    embeddingModel: "Embedding Models",
    input: ["Input"],
  },
})

from pipedream import Pipedream

pd = Pipedream(
    client_id="{oauth_client_id}",
    client_secret="{oauth_client_secret}",
    project_id="{project_id}",
    project_environment="production",
)

result = pd.actions.run(
    id="x_ai-create-embeddings",
    external_user_id="{external_user_id}",  # any stable ID for this user in your system
    configured_props={
        "x_ai": {"authProvisionId": "apn_xxxxxxx"},
        "embeddingModel": "Embedding Models",
        "input": ["Input"],
    },
)

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": "x_ai-create-embeddings",
    "configured_props": {
      "x_ai": { "authProvisionId": "apn_xxxxxxx" },
      "embeddingModel": "Embedding Models",
      "input": ["Input"]
    }
  }'