Mindee

A workflow step names the app and the action, and the editor fills in the connection when you pick one. This is the Step shape from the workflow spec, carrying Mindee's real ids.

{
  "manifestVersion": "2",
  "name": "mindee-example",
  "steps": [
    {
      "id": "classification-enqueue",
      "uses": {
        "app": "io.w6w.mindee",
        "action": "classification-enqueue",
        "connection": "conn_YOUR_CONNECTION_ID"
      },
      "with": {
        "modelId": "<modelId>"
      }
    }
  ]
}

Here are some of the things you can do

• Enqueue Classification

  perform
  classification-enqueue

• Get Classification Result

  read
  classification-result-get

• Enqueue Crop

  perform
  crop-enqueue

• Get Crop Result

  read
  crop-result-get

• Enqueue Extraction

  perform
  extraction-enqueue

+11 more actions available

Every app-specific value here is a blank you have to fill in. An app action is reached through the connection that authenticates it, so the address is a connection id, not the app id — and connections belong to your account, so a public page cannot know yours. Create one for Mindee, then fill in the three blanks: conn_YOUR_CONNECTION_ID, the action key, and the parameters that action declares. The call itself is real — the shape is transcribed from the studio's own snippet builder, which prints the same kind of blanks — but nothing in it is specific to Mindee. The Workflow tab is where this app's real ids are.

npm install @w6w/sdk

yarn add @w6w/sdk

pnpm add @w6w/sdk

deno add npm:@w6w/sdk

import { W6wClient, isActionRun } from "@w6w/sdk";

// Reads W6W_BASE_URL and W6W_TOKEN from the environment when omitted.
const client = new W6wClient();

const envelope = await client.run({
  urn: "conn_YOUR_CONNECTION_ID",
  action: "classification-enqueue",
  payload: {
    modelId: "<value>",
    // file: "<value>",
    // url: "<value>",
    // fileName: "<value>",
    // fileMimeType: "<value>",
    // webhookIds: "<value>",
    // alias: "<value>",
  },
});

if (isActionRun(envelope)) console.log(envelope.value);

npm install -g @w6w/cli

w6w run conn_YOUR_CONNECTION_ID --action classification-enqueue --payload '{"modelId":"<value>"}'

Give an AI agent Mindee — without giving it Mindee's credentials. One MCP endpoint exposes every app, function and workflow the caller is entitled to, as tools it can discover and run. Access is granted per team while we onboard.

{
  "name": "w6w_invoke",
  "arguments": {
    "ref": "app:io.w6w.mindee#classification-enqueue",
    "input": {
      "modelId": "<modelId>"
    }
  }
}

Every tool names its target with a single ref. The app: form above doesn't name a connection at all — the host resolves which of the caller's Mindee connections to sign with, and refuses rather than guesses when the answer is ambiguous.

What the agent gets

The MCP surface is part of the hosted platform. Mindee itself is MIT, and the runtime that executes it is source-available (FSL).

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