FORRT Research

forrt-research-mcp

An MCP server for producing verifiable FORRT nanopublication chains — the tools a researcher needs while doing the work, not while looking for it. It serves all three shapes of study on the same rails: reproduction, replication, and research that starts from scratch.

It is the third of three servers that compose:

Built for the workflow in forrt-replication-template, but it needs nothing from that repo — any agent can call it.

Scope: reproduction, replication, and research from scratch

All three work here, and they use the same chain:

anchor → AIDA → Claim → Study → Outcome → CiTO

Step 01 is one of three anchors, and they are not variants of one form. Which anchor fits is independent of whether the study is a reproduction, a replication or original research:

The three share no field ids whatsoever, so call template_fields on the anchor you are actually using rather than assuming they match. The pico_question_type vocabulary is named for PICO deliberately: a PCC question has no type to look up.

verify_quote applies to the Quote anchor only — and that is the one anchor with a dedicated tool, because a quotation is the one field whose correctness can be *proved* rather than reviewed.

constellation and prior_work surface a question anchor with its framework, label, full question text and its framework's components — PICO's population / intervention / comparator / outcome, PCC's population / concept / context. Question nodes keep all of that in a question object and leave their top-level label empty, so anything reading them like a quote returns nothing. Tested against two real published question nanopubs.

For a study starting from scratch, the Claim is your own hypothesis, derived from your own question or from the work you are building on. The FORRT Claim template's source is optional, so it needs no external paper — and the Claim-before-Study order then reads as pre-registration, not as a mismatch. verify_chain takes a mode (auto / replication / reproduction / new_research) that changes only what is *required*: from-scratch research has no existing work to cite, so no CiTO step and no cited DOI are expected.

The one place the templates still assume an original is the study_type vocabulary on 04_study, whose three terms are all replication-flavoured (Replication Study, Reproduction Study, or both). There is no term for *an original study testing its own claim*. Three field prompts read oddly too — scope and methodology say "is reproduced/replicated", and the Outcome's conclusion says "about the original claim" — but they are only wording; validationStatus (validated / partially supported / contradicted / inconclusive / not tested) describes testing your own hypothesis perfectly well.

So closing the gap is plausibly one added vocabulary term and three reworded prompts, not a new template family. When that lands, this server picks it up with no code change: template_fields and vocabulary fetch live, and driftedFromSnapshot flags the supersession so the vendored copy gets re-cut.

A note on using "Reproduction Study" for from-scratch work. It is a

reasonable workaround while the vocabulary lacks a better term, but the

template means the replication-science sense — *"direct reproduction: same

methodology, same tools"*, i.e. re-running someone else's analysis — not the

RSE sense of "my work is reproducible". Downstream consumers read it the first

way: replication-radar's verdict overlay and verified_claims will present

the study as verification of an existing claim.

Why a server and not a prompt

Two jobs here look like reasoning but are not, and doing them in an agent loop makes them unreproducible and expensive:

1. Reading a published chain. /np/constellation walks the FORRT citation graph bidirectionally and returns everything it reaches. For a single marine-heatwave chain that is 330 KB, 98 nodes and 1012 edges — of which 64 nodes are AIDA statements belonging to entirely different studies. Handing that to an agent burns its context and invites it to reason over another paper's claims. constellation returns the same chain in ~16 KB (4.7 %).

2. Checking a quotation is real. A FORRT Quote nanopub must be verbatim. That is a string search, not a judgement — so it should be a tool that cannot be talked out of its answer, and that anyone can re-run to get the same result.

What it does not do

It does not search papers (that is the OpenAIRE MCP), rank replication targets (that is replication-radar), or write nanopub content. It also does not *extract* claims: choosing which sentence carries a paper's headline claim is a judgement, and wrapping a judgement in a tool would not make it reproducible — a model behind a tool boundary is exactly as non-deterministic as one in the agent loop. The division this server is built around:

Install

pipx install forrt-research-mcp

claude mcp add forrt-research -s user -- forrt-research-mcp

User-scoped (-s user) so it is available in every session and folder, and does not clash with a per-repo config. For other agents, the stdio command is forrt-research-mcp.

# optional

export SCIENCELIVE_API_BASE="https://api.sciencelive4all.org" # default (production) export SCIENCELIVE_API_KEY="sl_…" # /np/constellation is a public read

The default base is production. To test against the dev deployment, set

SCIENCELIVE_API_BASE=https://api-dev.sciencelive4all.org. A constellation

that nobody has requested recently can take ~60 s to build; after that it is

cached for 4 h and returns in well under a second.

Tools

verify_quote(pdf_path, quotation)

Proves a candidate quotation is in a source PDF before it is published as verbatim. Returns a graded verdict with page, character offsets and the file's SHA-256:

Every tier canonicalises *formatting only* — never words, digits or order. A quotation with one digit changed scores ~0.91 similarity against the source and is still not_found; on a miss, closest.text_in_pdf shows what the paper actually says there.

A tier below exact is normal. PDF extraction inserts line breaks, loses hyphens, and sometimes breaks words apart entirely:

• the quotation published in the real marine-heatwave chain matches only at extraction_tolerant, because pypdf reads the paper's 35-year as 35year and (p < as ( p <;
• Hundhausen et al. 2024 renders its own abstract as CP en semble, largest c hanges, prec ipitation — spaces *inside* words, which no punctuation rule can undo. That needs whitespace_insensitive, which deletes every space and therefore does not verify word boundaries; it declines to run below 40 characters, where two short texts could collide.

"Character-for-character" is not literally achievable against extracted PDF text, which is why the result is graded rather than boolean.

Words split across a line break (convection-\npermitting) are rejoined at the normalized tier. A *suspended* hyphen (15- and 30-minute) is deliberately NOT rejoined — the rule requires a line break, because joining those would corrupt the text.

constellation(uri, depth=5, max_nodes=80)

The FORRT chain(s) reachable from a published nanopub URI, projected to agent-size: chains with their steps in chain order, the apex CiTO, any Research Synthesis, and the Quote/Question anchors attributable to this paper.

Read citedPaper, not the API's top-level paperDoi — see *Upstream quirks* below.

stepsPresent legitimately omits steps: a CiTO at the apex of a constellation is hoisted out of its chain, and Quote/AIDA anchors are often not enumerated. Missing does not mean unpublished.

prior_work(uri)

What has already been claimed about a paper — the starting point for new work, replication or otherwise. Per completed chain: claim type, scope, method, deviations, verdict, confidence, repository, and limitations.

limitations is the field to read most carefully. It is where previous authors stated, in signed and immutable words, what their study did *not* cover — which is often exactly where the next study begins. In the marine-heatwave chain it records that the paper's better-known 54 % headline describes a different analysis over a different period and was not tested.

constellation_raw(uri, …)

The unprojected response, for debugging the graph or an upstream data problem. Large; prefer constellation.

template_fields(step, live=True) · vocabulary(name, live=True) · list_schemas()

A nanopub template is the schema for its chain step, so these turn "never invent a field name" and "never invent a claim type" from rules an agent has to remember into a lookup that can only return real values.

template_fields returns the real field ids, prompts, required/repeatable flags, and the regex / prefix / datatype constraints — which is where the Quote template's character cap actually lives, rather than in a hand-written doc that drifts. step accepts 05_outcome, 05, or outcome.

vocabulary returns the allowed values of a controlled vocabulary, taken from the real restricted-choice field:

Both fetch live by default and fall back to a **bun