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DAG Studio MCP

OfficialLive

by Black-Swan-Causal-Labs · JavaScript

Causal DAG analysis: backdoor paths, adjustment sets, bias simulation. Validated against dagitty.

dagstudio-mcp (Model Context Protocol) Server

The com.blackswancausallabs/dagstudio-mcp Model Context Protocol server enables AI agents to construct, analyze, and validate causal directed acyclic graphs (DAGs). It uses the same DAG causal-inference engine behind the DAG Studio canvas and is validated against dagitty, covering backdoor paths, adjustment sets, and bias simulation.

🛠️ Key Features

  • Causal DAG analysis
  • Backdoor path identification
  • Adjustment set support
  • Bias simulation
  • Validation against dagitty
  • Model Context Protocol (MCP) integration

🚀 Use Cases

  • Epidemiology causal-inference workflows
  • Real-world evidence DAG development
  • Agent-driven DAG construction and analysis

⚡ Developer Benefits

  • Reuses the DAG Studio causal-inference engine
  • Works with agents via MCP
  • Consistent DAG validation using dagitty

⚠️ Limitations

  • Documentation excerpt does not specify additional tools, configuration options, or runtime constraints

Topics

  • causal-inference, dag, dagitty, epidemiology, mcp, model-context-protocol, real-world-evidence

Topics

causal-inferencedagdagittyepidemiologymcpmodel-context-protocolreal-world-evidence