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:

• Quotes resolve or die. Every quote is matched to character offsets in the 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.
• Absence is searched, not asserted. A manuscript_absent answer names a cue; the server runs the search and attaches the record — terms, sections, hit count. A prose claim that you looked is refused.
• Judgements are computed. No tool accepts a domain judgement as input. The 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.

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 set_prespecified_confounders 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 specify_result 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