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Dagster MCP Server

Name: Dagster
Availability: InStock
Author: Vinkius

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Orchestrate data pipelines via Dagster — monitor jobs, track runs, manage software-defined assets, and audit schedules directly from any AI agent.

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What is the Dagster MCP Server?

The Dagster MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Dagster via 6 tools. Orchestrate data pipelines via Dagster — monitor jobs, track runs, manage software-defined assets, and audit schedules directly from any AI agent. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.

Built-in capabilities (6)

get_runlist_assetslist_jobslist_runslist_scheduleslist_sensors

Tools for your AI Agents to operate Dagster

Ask your AI agent "List all jobs in my Dagster deployment" and get the answer without opening a single dashboard. With 6 tools connected to real Dagster data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.

Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.

Why teams choose Vinkius

One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.

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Dagster MCP Server capabilities

6 tools

get_run

Get run details from Dagster

list_assets

List all assets from Dagster

list_jobs

List all jobs from Dagster

list_runs

List recent runs from Dagster

list_schedules

List all schedules from Dagster

list_sensors

List all sensors from Dagster

What the Dagster MCP Server unlocks

Connect your Dagster (Plus or open-source) instance to any AI agent and take full control of your data orchestration and asset management through natural conversation.

What you can do

Job Orchestration — List and audit all data jobs available in your Dagster server to understand active pipeline boundaries
Run Monitoring — Fetch chronological history of recent job runs and retrieve detailed status and execution logs for specific run IDs
Asset Tracking — Enumerate software-defined assets to identify data dependencies and verify physical storage mappings
Schedules & Sensors — List all configured job schedules and active sensors listening for external events to audit automation triggers
Environment Audit — Identify deployment boundaries and verify instance connectivity across Dagster Plus or self-hosted clusters

How it works

1. Subscribe to this server
2. Enter your Dagster URL and User API Token (found in Deployment Settings > Tokens)
3. Start managing your data pipelines from Claude, Cursor, or any MCP-compatible client

Who is this for?

Data Engineers — monitor pipeline health and identify failed runs without leaving the chat or IDE
Analytics Engineers — track software-defined assets and verify data freshness in real-time
Data Platform Teams — audit job schedules and sensor configurations across organizational deployments
SREs — monitor Dagster agent health and verify instance connectivity through natural language

Frequently asked questions about the Dagster MCP Server

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

Yes. Use the 'list_assets' tool. 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' tool. 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' tools. Your agent will pull the active automation triggers, allowing you to audit which jobs are scheduled and which sensors are listening for external events.