Dagstudio MCP server

What it does

MCP server for causal directed acyclic graph (DAG) analysis. It provides tools to construct, analyze, and validate DAGs using the same engine that powers DAG Studio, including backdoor path identification, adjustment set computation, bias simulation, and effect modification classification. For researchers and analysts working with causal inference.

• Identify backdoor paths and compute minimal sufficient adjustment sets for a causal DAG to determine which variables to control for in observational studies.
• Simulate data from a DAG under specified structural coefficients and compute empirical bias of an adjustment strategy against the simulated truth.
• Parse dagitty DSL notation into a structured DAG model and generate R or Python analysis code for causal inference workflows.

Tools this server exposes

Tool	Does
analyze_dag	Identify backdoor paths, compute minimal sufficient adjustment sets, and assess identifiability of causal effects.
parse_dagitty	Convert dagitty DSL syntax (raw or R-wrapped) into the structured DAG model.
generate_code	Generate R or Python analysis code for a DAG and produce a shareable DAG Studio URL.
check_overadjustment	Detect problematic adjustment for mediators, colliders, and descendants of the exposure variable.
simulate_data	Generate synthetic data from a DAG under user-specified structural coefficients.
compute_bias	Measure the empirical bias of an adjustment strategy by comparing estimates to simulated ground truth.
classify_effect_modification	Classify effect-modifier structures as direct, indirect, proxy, common-cause, or pure interaction.
get_canonical_example	Retrieve canonical teaching DAGs covering confounding, M-bias, frontdoor criterion, and other structures.
validate_engine	Run the full canonical validation suite against Pearl theory and dagitty, and report engine version.

Before you enable it

An MCP server runs with whatever access you give it. Start with a development account rather than production, and check which tools the server exposes before you let an agent call them unattended.