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Connect Dagster 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. Manage your entire data pipeline directly from your AI agent.

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 Dagster.

  1. 01

    List schedules

    This capability pulls a full list of all configured schedules from your Dagster instance.

  2. 02

    List runs

    Use this to see a history of recent job executions.

  3. 03

    List sensors

    This capability retrieves all active sensors currently listening for events in Dagster.

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through Dagster.

  1. 04

    Get run

    This capability fetches specific details and execution data for a single run ID.

  2. 05

    List assets

    This capability provides a list of all software-defined assets in your environment.

  3. 06

    List jobs

    This capability returns a list of all available jobs within your Dagster deployment.

Real work

What teams actually run

01

Troubleshooting Failures

When a job fails, you ask your agent for the run details and logs to find the error immediately.

02

Asset Freshness Checks

You can verify if a specific software-defined asset has been updated recently.

03

Automation Audits

You can quickly list all active sensors to ensure your event-driven pipelines are running.

04

Deployment Oversight

You can check the list of available jobs to understand the scope of your current deployment.

Automate a task

Put Dagster 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

Dagster 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 Dagster 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

841ms average. Fast in production.

Dagster is checked daily against the live service.

Daily averagePeak 1134ms
Oct 3Today
Fastest day
653ms
Slowest day
1134ms
14-day trend
Slowing+40%

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 Dagster, so you can see the experience inside your AI.

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

Dagster Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_9Cla5bbOzNXXdswxQ5yhHdcbDLhh8oRbE80hiC24/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 — Dagster capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "dagster-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_9Cla5bbOzNXXdswxQ5yhHdcbDLhh8oRbE80hiC24/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 Dagster in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Dagster owners hand off.

This MCP is built for technical teams managing complex data workflows who need fast, conversational access to pipeline health.

  • 01

    Data Engineers

    They use the agent to monitor pipeline health and troubleshoot failed runs without switching contexts.

  • 02

    Analytics Engineers

    They use the agent to track software-defined assets and check if data is fresh.

  • 03

    SREs

    They use the agent to verify instance connectivity and monitor Dagster agent health.

FAQ

Questions Dagster owners ask.

  • 01

    Does this work with Dagster Open Source?

    Yes, this MCP works with both Dagster Plus and self-hosted open-source instances.

  • 02

    What information do I need to provide?

    You will need your Dagster URL and a User API Token, which you can find in your Deployment Settings under Tokens.

  • 03

    Can I see error logs through my AI client?

    Yes, once you identify a specific run ID, your agent can retrieve the detailed execution logs for you.

  • 04

    Which AI clients can I use with this MCP?

    You can use any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 05

    How does this help with asset management?

    The MCP allows your agent to enumerate software-defined assets so you can verify dependencies and storage mappings through chat.

  • 06

    Can my agent list all software-defined assets in Dagster?

    Yes. Use the 'list_assets' capability. Your agent will retrieve all software-defined assets, allowing you to identify data dependencies and verify physical storage mappings within your pipelines.

  • 07

    How do I check the status of a specific job run?

    Provide the 'run_id' to the 'get_run' capability. Your agent will fetch detailed information for that specific execution, including status (Success, Failure, In Progress) and detailed execution logs.

  • 08

    Can I see active sensors and schedules via the agent?

    Absolutely. Use the 'list_schedules' and 'list_sensors' capabilities. Your agent will pull the active automation triggers, allowing you to audit which jobs are scheduled and which sensors are listening for external events.

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