"author:Black-Swan-Causal-Labs" matching MCP servers:

MCP server for the DAG Studio causal-inference engine, enabling AI agents to construct, analyze, and validate causal directed acyclic graphs (DAGs) through tools for analysis, data simulation, and code generation.

Enables querying FDA regulatory metadata for drugs, biologics, and medical devices through the openFDA API, including resolving application numbers and product names to authoritative regulatory details.

Enables automated assessment of research manuscripts against the TARGET reporting guideline for target trial emulation, providing item-by-item scoring with evidence and provenance.

An MCP server implementing the ROBINS-I V2 framework for risk-of-bias assessment in non-randomized studies, with deterministic algorithms and full provenance. It enables users to parse study documents, specify target trial results, answer signalling questions with evidence-bound quotes, and compute or override domain judgements.

Enables design-correct, conversational analysis of NHANES public-use data by automating file discovery, merging, weight selection, pooling, survey variance estimation, and mortality-linked Cox models.

Enables retrieval and structural analysis of FDA regulations.gov dockets: searching dockets, pulling comments and attachments into a local cache, extracting sectioned guidance text, and computing section-aligned draft-versus-final guidance diffs. All results are deterministic and cache-first, with no model calls in the server.