Replication Radar
LocalAbout Replication Radar
Replication Radar is a research discovery service for finding impact-ranked replication targets and checking whether claims have already been tested. It combines OpenAIRE Graph records with software reuse signals and Science Live nanopublication verdicts, and is available as a web app and MCP server.
Key features
- 01Ranks replication targets by impact
- 02Overlays live verification verdicts
- 03Finds software independent of original authors
- 04Retrieves claims with recorded verdicts
- 05Provides FORRT replication-template guidance
Use cases
- 01Build a replication shortlist for a research topic
- 02Check whether a paper's claim has been tested
- 03Find independent software for a replication
MCP support
The MCP server exposes the Radar engine's discovery and verification tools to agents, including target ranking, software search, replication status, and verified claims.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
uvx replication-radarGITHUB_TOKENSecretOptional GitHub token for higher API rate limits (RADAR_GITHUB_TOKEN also accepted)RADAR_OPENAIRE_BASEOpenAIRE Graph API base (default: https://api.openaire.eu/graph/v1)RADAR_NANOPUB_SPARQLNanopub SPARQL endpoint (default: https://query.knowledgepixels.com/repo/full)RADAR_HTTP_TIMEOUTPer-request timeout in seconds (default: 30)Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
6Saved tool list · updated 3d ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| limit | integer | No | |
| topic | string | Yes |
Details
From the project READMEReplication Radar
🔗 Live demo → https://openaire-hackathon.netlify.app
▶ Watch the 3-min demo → https://youtu.be/hVyLafY3Y3E · reproduce it step by step → https://openaire-hackathon.netlify.app/demo.html
A tool that makes the OpenAIRE Graph more useful for replication. Search a research field and it answers the question the Graph structurally cannot: what high-impact work is worth replicating, has it already been independently checked — with what verdict — and is the software reusable?
Ships as a live web app (the link above — pure static, queries OpenAIRE + the nanopub network + GitHub/Software Heritage from the browser) and an MCP server (this package) that exposes the same engine to any agent. Built for the OpenAIRE AI Hackathon (Theme B), CC-BY.
OpenAIRE's only value signal is citation-popularity (BIP! influence / popularity / impulse, classes C1–C5) — paper-bound, and orthogonal to whether a claim is true. The Radar joins three sources to add a replication layer on top:
- OpenAIRE Graph — impact-ranks candidate papers (
api.openaire.eu/graph/v1). - Software Heritage + repo signals — surfaces reusable method software.
- Science Live nanopub verdicts — the "already checked → did it hold" overlay.
OpenAIRE AI Hackathon · Theme B (Build) · CC-BY. Built to be reused through the forrt-replication-template: discovery at the start of a replication, where the template's existing skills handle the nanopub chain at the end.
Tools
| Tool | What it answers |
|---|---|
radar(topic) | Impact-ranked replication targets in a field — each OPEN (opportunity) or VERIFIED (done, with verdict) + independent tooling + funder context |
find_independent_software(doi, topic) | Reusable engines not authored by the original team (author-disjoint = replication, not reproduction), ranked by reuse signal — repo · Software Heritage · downloads · GitHub stars — not citations (returns stars + rank_score) |
replication_status(doi) | Has this DOI been replicated, did it hold? Verdict(s) — live from the nanopub network, any signer — with status, CiTO relation, repo, and signed Outcome/CiTO nanopub links; open if not |
verified_claims() | The whole verified-knowledge corpus — every claim the network holds a verdict for (author-agnostic) |
replication_template(doi, topic, owner) | The FORRT replication template (the produce half) — the scaffold repo, the workflow, and a suggested <topic>-replication repo name (checks availability under owner) |
find_dataset(topic) | Hand-off to the OpenAIRE MCP for datasets — replication-radar doesn't search datasets; this says how to find a citable dataset DOI there |
The verdict tools pull live from the nanopub network (the FORRT Outcome/CiTO templates on
query.knowledgepixels.com); the bundled verdicts.json is an offline fallback. So the MCP is the
verified-knowledge layer — pair it with the OpenAIRE MCP and an agent has both the structural
Graph and "has this been checked, and did it hold".
The reproduction-vs-replication distinction, made computable
A reproduction re-runs the original code; a replication tests the same claim by a
different route. So the Radar filters tooling by author-disjointness from the
original paper — e.g. for Phillips et al. 2009, the dismo package (co-authored by
Phillips & Elith) is flagged rooted / non-independent, while biomod2 and jSDM
are independent. That filter is the difference between the two, and it's the thing
that makes this replication-aware rather than just "find the code".
Run
pip install -e . # installs the `mcp` runtime
python -m replication_radar.server # stdio MCP server
Add to an MCP client (.mcp.json):
{ "mcpServers": {
"replication-radar": { "command": "python", "args": ["-m", "replication_radar.server"] }
} }
The core (OpenAIRE client + radar logic) is stdlib-only — try it without the MCP runtime:
PYTHONPATH=src python3 demo_sdm.py # live vertical-slice demo on SDM
Configuration
| Env var | Default | Purpose |
|---|---|---|
RADAR_OPENAIRE_BASE | https://api.openaire.eu/graph/v1 | Swap to the Alien AI-Gateway or a mirror — the Radar is endpoint-agnostic |
RADAR_HTTP_TIMEOUT | 30 | Per-request timeout (s) |
Known limits (v1, honest)
- Keyword-bound discovery. OpenAIRE free-text terms are AND-ed; long queries return nothing. Use short topics. The VERIFIED overlay is guaranteed (resolved from the verdict index directly), but OPEN-target recall depends on the query.
- No graph-relation traversal on the public API (paper→its software/data/grant edges aren't exposed): tooling/data are matched heuristically by topic + author independence, not by a hard relation. Upgrades cleanly if a gateway exposes relations.
- Funder context is field-level, not per-paper (per-paper funder attribution is not reachable); budgets are frequently reported as 0 in records.
- The verdict index ships 6 source works / 12 chains (Science Live). Extend
data/verdicts.jsonto grow coverage.
Comments
New to MCP?
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