Dagster Connector for AI agents.
6 live capabilities
Manage and monitor your data pipelines and orchestration assets in real time.
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Why people use Dagster
Dagster for Faster Data Pipeline Monitoring
This Connector brings that entire view into your chat window. You can just ask your agent for the status of the last five runs or get a summary of all active sensors. You get a unified view of your orchestration layer without ever leaving your workspace.
What Vinkius changes
You get a conversational interface for your entire data orchestration layer.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Debugging a failed pipeline
A data engineer asks the agent to show the logs for the last failed run of the daily ETL job to identify a schema mismatch.
- Real-world use case 02
Auditing a new deployment
A platform team asks the agent to list all active sensors to ensure no triggers were missed during a migration.
- Real-world use case 03
Checking data freshness
An analytics engineer asks what assets are defined and if the latest run was successful before updating a dashboard.
Complete set · 6capabilities
The complete Dagster capability set.
These are the exact actions your AI can choose when you ask it to work with Dagster.
01—03
3 capabilities in this set.
Part of 6 available through Dagster.
- 01 Capability
List schedules
List all configured job schedules. This helps you audit your automation and timing across the project.
- 02 Capability
List jobs
Get a full list of all data jobs in your Dagster environment. Use this to understand your active pipeline boundaries.
- 03 Capability
List runs
Pull a chronological history of recent job executions. It's the fastest way to see what just finished.
04—06
3 capabilities in this set.
Part of 6 available through Dagster.
- 04 Capability
Get run
Retrieve detailed status and execution logs for a specific run ID. This is your go-to for debugging failures.
- 05 Capability
List assets
Enumerate all software-defined assets. Use this to identify data dependencies and storage mappings.
- 06 Capability
List sensors
See all active sensors listening for external events. This helps you audit your automation triggers.
Set up in minutes
One URL. Then ask Dagster to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Dagster from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_9Cla5bbOzNXXdswxQ5yhHdcbDLhh8oRbE80hiC24/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Dagster, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Dagster for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_9Cla5bbOzNXXdswxQ5yhHdcbDLhh8oRbE80hiC24/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Dagster URL.
- Step 03
Save and start
Save the connection and enable Dagster in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"dagster": {
"url": "https://edge.vinkius.com/vk_preview_9Cla5bbOzNXXdswxQ5yhHdcbDLhh8oRbE80hiC24/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Dagster
Open Agent mode in chat and ask: "Using Dagster, help me...". 6 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"dagster": {
"url": "https://edge.vinkius.com/vk_preview_9Cla5bbOzNXXdswxQ5yhHdcbDLhh8oRbE80hiC24/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Dagster
Ask Copilot: "Using Dagster, help me...". 6 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"dagster": {
"url": "https://edge.vinkius.com/vk_preview_9Cla5bbOzNXXdswxQ5yhHdcbDLhh8oRbE80hiC24/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Dagster
Open Cascade and ask: "Using Dagster, help me...". 6 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"dagster": {
"url": "https://edge.vinkius.com/vk_preview_9Cla5bbOzNXXdswxQ5yhHdcbDLhh8oRbE80hiC24/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Dagster
Ask Cline: "Using Dagster, help me...". 6 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add dagster --transport http "https://edge.vinkius.com/vk_preview_9Cla5bbOzNXXdswxQ5yhHdcbDLhh8oRbE80hiC24/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Dagster
Ask Claude: "Using Dagster, show me...". 6 tools are ready
Where the request belongs
Work Dagster can move forward.
This is for the data engineer who's tired of clicking through dashboards at 2am to find out why a pipeline stalled, or the platform lead who needs to audit complex automation triggers across a massive enterprise deployment.
Data Engineer
Uses this to quickly pull logs for failed runs and check job statuses without leaving their IDE.
Analytics Engineer
Verifies data freshness and maps out software-defined assets to ensure upstream changes don't break downstream tables.
Data Platform Team
Audits job schedules and sensor configurations across multiple production environments to ensure consistency.
SRE
Monitors agent health and verifies instance connectivity through natural language commands during incidents.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsPrefect
Bring your data orchestration into your AI. audit Python pipelines, debug failed runs, and inspect Prefect Work Pools natively.
Integrate.io (ETL & Data Integration)
Manage data pipelines via Integrate.io. list pipelines, monitor job runs, and audit data transformations.
Dagger (Programmable CI)
Build, test, and deploy using Dagger's programmable CI engine. Execute GraphQL queries, manage containers, and orchestrate pipelines directly from your AI agent.
Dataiku DSS
Manage data science via Dataiku. list projects and datasets, track pipeline jobs, run automation scenarios, and monitor ML models directly from any AI agent.
Portable.io
Manage your Portable ETL pipelines directly via your AI agent. monitor flows, sync runs, and destination details seamlessly.
Matillion (Cloud Data Integration & ELT)
Manage data pipelines via Matillion. audit ETL workflows, track execution statuses, and monitor cloud environments.
Bring your own AI
Change the model, client or framework. Keep Dagster connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Dagster.
The practical details behind the request, access and result.
Can I use Dagster MCP to see if my pipelines failed?
Yes, you can ask your agent to pull the history of recent runs to see exactly which ones failed and what their current status is.
Does Dagster MCP work with my self-hosted instance?
Yes, it works with both Dagster Plus and self-hosted clusters by using your unique URL and API token.
Can I use this to find specific error logs?
You can ask the agent to fetch the details for a specific run ID to see the execution logs and identify why a step failed.
How do I connect my Dagster account?
You just need your Dagster URL and a User API Token, which you can find in your Deployment Settings.
Can I see all my data assets with this?
Yes, you can enumerate all software-defined assets to see your dependencies and storage mappings in plain English.
Does this help with auditing my schedules?
It lets you list all configured job schedules and sensors to see how your automation is triggered across your project.
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.
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.
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.
One connection away
Give your agent a direct line to Dagster.
Connect Dagster once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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