Get started with Unstructured Transform for Vercel AI SDK

npm install ai @ai-sdk/anthropic @ai-sdk/mcp zod
npm install --save-dev tsx

export UNSTRUCTURED_API_KEY="<your-unstructured-api-key>"

import { createMCPClient } from '@ai-sdk/mcp';

const mcpClient = await createMCPClient({
  transport: {
    type: 'http',
    url: 'https://mcp.transform.unstructured.io',
    headers: { Authorization: `Bearer ${process.env.UNSTRUCTURED_API_KEY}` },
  },
});

// Loads the Transform tools: request_file_upload_url, start_transform_job,
// check_job_status, get_job_results, suggest_extraction_schema_for_file,
// start_extraction_job, and get_instructions.
const tools = await mcpClient.tools();

import { createMCPClient } from '@ai-sdk/mcp';
import { anthropic } from '@ai-sdk/anthropic';
import { generateText, stepCountIs, tool } from 'ai';
import { z } from 'zod';

const TRANSFORM_MCP_URL = 'https://mcp.transform.unstructured.io';

const SYSTEM_PROMPT = `You partition documents with Unstructured's Transform MCP tools.
Transforms are ASYNC jobs. Follow this exact sequence:
1. Call start_transform_job with the document URL, output format markdown.
2. Call the "wait" tool (a few seconds), THEN check_job_status. Repeat
   wait -> check until the status is COMPLETED. Never poll without waiting first.
3. Call get_job_results, then downloadText on the first file's download_url
   to read the Markdown. Summarize the content for the user.`;

const wait = tool({
  description:
    'Pause for a few seconds before polling an async job again. Use between check_job_status calls.',
  inputSchema: z.object({ seconds: z.number().min(1).max(10) }),
  execute: async ({ seconds }) => {
    await new Promise((resolve) => setTimeout(resolve, seconds * 1000));
    return { waited: seconds };
  },
});

// Restrict downloads to the Transform host (where the pre-signed download_url is
// served) so a crafted prompt cannot turn this tool into an SSRF vector.
const ALLOWED_DOWNLOAD_HOST = new URL(TRANSFORM_MCP_URL).host;

const downloadText = tool({
  description:
    'Download transformed output from a pre-signed download_url with an HTTP GET.',
  inputSchema: z.object({ url: z.string().url() }),
  execute: async ({ url }) => {
    const parsed = new URL(url);
    if (parsed.protocol !== 'https:' || parsed.host !== ALLOWED_DOWNLOAD_HOST) {
      throw new Error(`Refusing to download from "${parsed.host}".`);
    }
    // The URL is pre-signed: do not send an Authorization header here.
    const response = await fetch(parsed);
    if (!response.ok) throw new Error(`Download failed: ${response.status}`);
    return await response.text();
  },
});

async function main() {
  const mcpClient = await createMCPClient({
    transport: {
      type: 'http',
      url: TRANSFORM_MCP_URL,
      headers: { Authorization: `Bearer ${process.env.UNSTRUCTURED_API_KEY}` },
    },
  });

  try {
    const tools = { ...(await mcpClient.tools()), wait, downloadText };

    const { text } = await generateText({
      model: anthropic('claude-opus-4-8'),
      system: SYSTEM_PROMPT,
      tools,
      // Async jobs need several wait -> poll cycles; give the loop room.
      stopWhen: stepCountIs(25),
      prompt:
        'Partition this document into clean markdown and summarize its sections. ' +
        'URL: https://raw.githubusercontent.com/Unstructured-IO/unstructured/main/example-docs/pdf/layout-parser-paper.pdf',
    });

    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main().catch((error) => {
  console.error(error);
  process.exit(1);
});

export ANTHROPIC_API_KEY="<your-anthropic-api-key>"

npx tsx transform-agent.ts

const EXTRACTION_SYSTEM_PROMPT = `You extract structured data with Unstructured's Transform MCP tools.
Follow this exact sequence:
1. Call start_transform_job with the document URL, and stages
   {"partition": {"strategy": "vlm"}} for an image, PowerPoint file, or PDF.
2. Call the "wait" tool, THEN check_job_status. Repeat until COMPLETED.
3. Call get_job_results and keep each file's output_ref. Do NOT downloadText it.
4. If the user gave you no schema, call suggest_extraction_schema_for_file with
   that output_ref and show the draft schema before extracting.
5. Call start_extraction_job with element_json_refs set to the output_refs, and
   schema_to_extract set to the JSON Schema passed as a JSON string.
6. Poll with wait -> check_job_status, then call get_job_results. Results come
   back inline, wrapped with filename, filetype, processed_date_utc, and
   source_file_uri alongside extracted_data. Report the filename with each
   object and do not strip that wrapper.`;