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Connect Unstructured to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Turn messy documents into clean data for your RAG workflows.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 6 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through Unstructured.

  1. 01

    Trigger workflow execution

    Triggers an immediate execution of a specific processing workflow. It returns a job ID so you can track the progress.

  2. 02

    List processing workflows

    Retrieves a list of all your end-to-end document processing pipelines.

  3. 03

    List workflow jobs

    Shows all active and historical workflow execution jobs. Use this to check if your recent data ingestions finished successfully.

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through Unstructured.

  1. 04

    Get workflow details

    Fetches the specific configuration settings for a single processing workflow.

  2. 05

    List data destinations

    Lists all configured target locations, such as Vector DBs or SQL databases, where your processed data is sent.

  3. 06

    List data sources

    Shows all configured remote data connectors, including S3 and GCS, where your documents are pulled from.

Real work

What teams actually run

01

RAG Pipeline Maintenance

Check if your latest document sync successfully populated your vector database.

02

On-demand Ingestion

Trigger a new processing job immediately after uploading files to an S3 bucket.

03

Workflow Auditing

Verify the source and destination mappings for existing document pipelines.

04

Error Troubleshooting

Identify why a specific document processing job failed by checking its execution ID.

Automate a task

Put Unstructured to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Unstructured works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Unstructured to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

916ms average. Fast in production.

Unstructured is checked daily against the live service.

Daily averagePeak 1113ms
Oct 3Today
Fastest day
720ms
Slowest day
1113ms
14-day trend
Improving-11%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Unstructured, so you can see the experience inside your AI.

It does not authenticate your account with Unstructured. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Unstructured Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_wLKl0zBun6GGEWOAXV2AtIEfq4BCwiQMTDSCBvt6/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Unstructured capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "unstructured-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_wLKl0zBun6GGEWOAXV2AtIEfq4BCwiQMTDSCBvt6/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Unstructured in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Unstructured owners hand off.

This MCP is built for technical teams managing large scale document processing and RAG pipelines.

  • 01

    Data Engineers

    They use the agent to trigger and troubleshoot ingestion workflows without opening the Unstructured dashboard.

  • 02

    AI Developers

    They monitor RAG pipelines to ensure vector databases stay populated with clean data.

  • 03

    MLOps Teams

    They track historical processing jobs to verify that scheduled syncs completed successfully.

FAQ

Questions Unstructured owners ask.

  • 01

    How do I connect this MCP to my agent?

    You subscribe to the MCP on Vinkius, enter your Unstructured API credentials, and then connect your client like Claude or Cursor in one click.

  • 02

    Can I trigger new data ingestions from my AI client?

    Yes, you can use the trigger_workflow_execution capability to start a processing job immediately.

  • 03

    What kind of data sources are supported?

    The MCP can list and interact with remote data connectors like S3, GCS, and SharePoint.

  • 04

    Can I see if my previous jobs failed?

    Yes, you can use the list_workflow_jobs capability to view both active and historical execution records.

  • 05

    Where does the processed data go?

    You can configure and view destinations such as Vector DBs or SQL databases through the list_data_destinations capability.

  • 06

    Can my AI agent trigger an immediate document processing job?

    Yes! If you have a workflow configured to pull files from an S3 bucket and load them into a Pinecone index, you can ask your agent to trigger workflow XYZ. It will start the execution and return the new Job ID, which you can use to track the progress.

  • 07

    How can I verify if my RAG pipelines are failing or succeeding?

    Ask your agent to list your workflow jobs. It will securely connect to Unstructured's engine and return historical and active executions, displaying statuses such as 'completed', 'failed', or 'in_progress'. This is extremely useful for MLOps engineers diagnosing ingestion alerts directly in their terminal.

  • 08

    Can I edit the destination database directly through the agent?

    This server is focused on auditing and executing your existing pipelines. Currently, you can list all connections (sources and destinations) and obtain their details, but creating or destructively modifying vector database connectors must be done inside the Unstructured dashboard for security.

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