Bring Data Orchestration
to LangChain
Create your Vinkius account to connect Dagster to LangChain and start using all 6 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Dagster MCP Server?
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
- Subscribe to this server
- Enter your Dagster URL and User API Token (found in Deployment Settings > Tokens)
- 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
Built-in capabilities (6)
Get run details from Dagster
List all assets from Dagster
List all jobs from Dagster
List recent runs from Dagster
List all schedules from Dagster
List all sensors from Dagster
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Dagster through native MCP adapters. Connect 6 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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The largest ecosystem of integrations, chains, and agents. combine Dagster MCP tools with 500+ LangChain components
- —
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Dagster queries for multi-turn workflows
Dagster in LangChain
Why run Dagster with Vinkius?
The Dagster connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 6 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect Dagster using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
Dagster and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect Dagster to LangChain through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
Dagster for LangChain
Every request between LangChain and Dagster is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
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.
How does LangChain connect to MCP servers?
Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
Which LangChain agent types work with MCP?
All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters
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