ROBINS-I V2 MCP server

robins-i-mcp

<!-- mcp-name: com.blackswancausallabs/robins-i-mcp -->

An MCP server implementing ROBINS-I V2 (Risk Of Bias In Non-randomized Studies – of Interventions, follow-up/cohort variant) as a deterministic, provenanced assessment engine.

Sibling to target-mcp, which scores how completely a target-trial-emulation study reports what the TARGET guideline requires. This one assesses risk of bias in one specific result. The two are complementary on the same paper.

The source is a draft. riskofbias.info presents the 20 November 2025

release of ROBINS-I V2 as still a draft, subject to change. Every report

stamps that in its provenance line. See NOTICE and TRANSCRIPTION-NOTES.md.

Follow-up cohort studies. "Follow-up" and "cohort" name one structural

property — a defined time zero, individuals followed forward under the

contrasted strategies — so read the property, not a design label. Target trial

emulations are the central use case and are cohort studies in exactly this

sense; both worked examples below are TTEs. Designs with no follow-up

structure are out. No variant for other designs is published yet. Note that

"Variant A / Variant B" inside the tool means the two forms of Domain 1

selected by C4 — not a study design.

What makes it different from asking a model

The model's contribution is bounded at answering signalling questions from the text. It cannot compute a judgement and it cannot invent evidence.

1  parse_document              PDF + supplement → SectionMap        deterministic
2  cue detection               where to look, per domain            deterministic
3  answer signalling questions quotes copied from the bundle        MODEL
4  evidence binding            quotes → offsets, or REJECT          deterministic
5  algorithms                  answers → domain → overall           deterministic
6  report + render             stamped artifact                     deterministic
7  human ratification          P1, reviewer-prior answers, overrides

Three rules are enforced at submission, and they are the point of the server:

ingested bundle through a three-pass ladder (exact → hyphen-relaxed → references-stripped), and the winning pass is recorded so a loose match is never silently equated with an exact one. An unresolvable quote is rejected with the nearest actual text.

• Quotes resolve or die. Every quote is matched to character offsets in the

cue; the server runs the search and attaches the record — terms, sections, hit count. A prose claim that you looked is refused.

• Absence is searched, not asserted. A manuscript_absent answer names a

six domain algorithms and the overall algorithm are explicit edge graphs traced from the published flowcharts. A human may override, with a recorded justification, and the report shows both values.

• Judgements are computed. No tool accepts a domain judgement as input. The

Two gates

P1 blocks domain 1. Question 1.1 asks whether all important confounding factors were controlled, and "important" is defined by the reviewer's prespecified list — not by the paper's covariate table. The server refuses to score domain 1 without setprespecifiedconfounders rather than silently substituting one for the other. A list you propose is a candidate: it enters the ratification queue until a human accepts it.

C4 selects domain 1's question set. Whether the analysis accounts for protocol deviations picks variant A (intention-to-treat, baseline confounding only) or variant B (per-protocol, baseline and time-varying confounding), so specifyresult requires it up front with no default. Judge it on what the analysis does*, not on the label the authors give their estimand — on the reference paper, the protocol table says "per-protocol effect" and the analysis is intention-to-treat.

Install

pip install robins-i-mcp

Shortened. The full README is on GitHub.