MCP

Give your agent Mistral AI tools

Every Mistral AI 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 Mistral AI 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": "mistral_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 Batch Job:
const result = await mcp.callTool({
  name: "mistral_ai-create-batch-job",
  arguments: {
    inputFiles: ["File IDs"],
    modelId: "Model ID",
  },
})

# 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": "mistral_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 Batch Job:
        result = await session.call_tool("mistral_ai-create-batch-job", {
            "inputFiles": ["File IDs"],
            "modelId": "Model ID",
        })

MCP guide →

API PROXY

Call the Mistral AI API directly

For an endpoint with no pre-built tool, the Connect proxy forwards your request to the Mistral AI 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.mistral.ai",
})

// Any allowed Mistral AI 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.mistral.ai

curl "https://api.pipedream.com/v1/connect/{project_id}/proxy/aHR0cHM6Ly9hcGkubWlzdHJhbC5haQ?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 Mistral AI actions from your backend

Connect a user's Mistral AI account once, then run Create Batch Job 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: "mistral_ai-create-batch-job",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    mistral_ai: { authProvisionId: "apn_xxxxxxx" },
    inputFiles: ["File IDs"],
    modelId: "Model ID",
  },
})

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="mistral_ai-create-batch-job",
    external_user_id="{external_user_id}",  # any stable ID for this user in your system
    configured_props={
        "mistral_ai": {"authProvisionId": "apn_xxxxxxx"},
        "inputFiles": ["File IDs"],
        "modelId": "Model ID",
    },
)

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": "mistral_ai-create-batch-job",
    "configured_props": {
      "mistral_ai": { "authProvisionId": "apn_xxxxxxx" },
      "inputFiles": ["File IDs"],
      "modelId": "Model ID"
    }
  }'