Unstructured MCP Server for Vercel AI SDK 6 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Unstructured through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token — get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Unstructured, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Unstructured MCP Server
Connect your Unstructured.io account to any AI agent to automate data ingestion and document processing pipelines seamlessly. Transform complex files into clean, AI-ready data without leaving your workflow.
The Vercel AI SDK gives every Unstructured tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 6 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Data Sources — List all configured remote data connectors (e.g. S3, GCS, SharePoint) to see where documents can be pulled from.
- Data Destinations — Browse target locations (like Vector DBs or SQL databases) where structured output is sent.
- Processing Workflows — List end-to-end pipelines, retrieve specific workflow configurations, and explore source-destination mappings.
- Job Execution — Manually trigger immediate document ingestion and partitioning jobs, and track their execution IDs.
- Job Monitoring — List active and historical workflow execution jobs to monitor the progress of your document processing tasks.
The Unstructured MCP Server exposes 6 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Unstructured to Vercel AI SDK via MCP
Follow these steps to integrate the Unstructured MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 6 tools from Unstructured and passes them to the LLM
Why Use Vercel AI SDK with the Unstructured MCP Server
Vercel AI SDK provides unique advantages when paired with Unstructured through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same Unstructured integration everywhere
Built-in streaming UI primitives let you display Unstructured tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Unstructured + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Unstructured MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Unstructured in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Unstructured tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Unstructured capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Unstructured through natural language queries
Unstructured MCP Tools for Vercel AI SDK (6)
These 6 tools become available when you connect Unstructured to Vercel AI SDK via MCP:
get_workflow_details
Retrieves configuration details for a specific processing workflow
list_data_destinations
g. Vector DBs, SQL). Lists all configured target locations for processed data
list_data_sources
Lists all configured remote data connectors (e.g. S3, GCS)
list_processing_workflows
Lists all end-to-end document processing pipelines
list_workflow_jobs
Lists all active and historical workflow execution jobs
trigger_workflow_execution
Returns a job ID. Manually triggers an immediate execution of a processing workflow
Example Prompts for Unstructured in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Unstructured immediately.
"Show me all our active destination connectors."
"List the historical processing jobs from today."
"Trigger the engineering onboarding workflow."
Troubleshooting Unstructured MCP Server with Vercel AI SDK
Common issues when connecting Unstructured to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpUnstructured + Vercel AI SDK FAQ
Common questions about integrating Unstructured MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Unstructured with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Unstructured to Vercel AI SDK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.