{"name":"com.blackswancausallabs/target-mcp","slug":"blackswancausallabs-target-mcp","title":"TARGET Checklist MCP","description":"Score how completely a target-trial-emulation study reports what the TARGET guideline requires.","url":"https://mcp.market/server/blackswancausallabs-target-mcp","rating":null,"grade":"B","score":82,"certified":false,"status":"active","category":"other","tags":[],"presence":{"score":17,"stars":0,"forks":0,"downloads_week":30,"last_push_at":"2026-08-23T00:22:52.000Z","license":"Apache-2.0"},"uptime":null,"claimed":false,"transport":"pypi","callable_via_gateway":false,"default_price_micros":0,"repository":"https://github.com/Black-Swan-Causal-Labs/target-mcp","website":null,"version":"0.2.0","remotes":[],"packages":[{"registryType":"pypi","registryBaseUrl":"https://pypi.org","identifier":"target-mcp","version":"0.2.0","transport":{"type":"stdio"}}],"tools":[{"name":"aggregate_corpus","description":"Roll up many assessments into per-item completeness rates plus coverage denominators (supplement-retrieval status, full-text availability, evidence- resolution rate). Pass an array of assessment objects as `assessments`, or use_session=true to aggregate every assessment produced this session. The completeness rates are only as valid as the sample and are not yet gold-standard calibrated.","write_action":false,"price_micros":0,"input_schema":null},{"name":"assess_manuscript","description":"Assess a manuscript against all applicable TARGET leaves in one batched pass. `document` is a path, raw text, or a text_sha256 returned by parse_manuscript.","write_action":false,"price_micros":0,"input_schema":null},{"name":"build_coding_sheet","description":"Emit blank per-paper coding sheets for human gold-standard coding: one row per applicable leaf with its intent and verdict boundaries and empty verdict/evidence/note fields. blind=true (default) withholds the instrument's verdict so coders are not anchored — use blind coding for the primary reference standard. Pass `assessments` or use_session=true.","write_action":false,"price_micros":0,"input_schema":null},{"name":"get_checklist","description":"Return the encoded TARGET checklist spec: 39 scoreable leaf subitems (grouped into the 21 published items) with intent, assessor notes, signal terms, pairing links, and applicability rules. Pass a version id to pin; omit for the current default.","write_action":false,"price_micros":0,"input_schema":null},{"name":"parse_manuscript","description":"PRIMARY entry point: parse a manuscript into a SectionMap with character-offset, source-tagged section spans.","write_action":false,"price_micros":0,"input_schema":null},{"name":"parse_pmcid","description":"CONVENIENCE / BATCH entry point: retrieve an open-access article from Europe PMC by PMCID and parse it. Reach for this in the corpus/batch case (no file in hand) or to auto-fetch an open-access paper's supplement; for a single manuscript you were given, use parse_manuscript instead. Fetches JATS main text plus (if available) PMC-hosted supplementary files, merged into one source-tagged SectionMap.","write_action":false,"price_micros":0,"input_schema":null},{"name":"render_checklist","description":"Render a finalized assessment as the completed TARGET checklist form: the 21 published items (39 leaf rows, in checklist order) with the published item wording and a Location-reported column derived from the resolved evidence spans. The default enriched view adds, per leaf, the instrument's verdict and the verbatim evidence quote that justifies the location; view='official' strips to the published","write_action":false,"price_micros":0,"input_schema":null},{"name":"render_checklist_docx","description":"Write the completed TARGET checklist to a Word (.docx) file and return it. Same content as render_checklist (published item wording + a Location-reported column from the resolved evidence spans; enriched view adds verdict and evidence), serialized as a submission-ready landscape table, one per manuscript section. Pass a full `assessment` object or the `manuscript_id` of one assessed this session.","write_action":true,"price_micros":0,"input_schema":null},{"name":"render_checklist_html","description":"Render the completed TARGET checklist as a self-contained HTML page — same content as render_checklist, styled to the Black Swan Causal Labs identity (canvas ground, one aligned table, verdict pills), viewable in any browser on any host. Returns the HTML string in `html` (show it inline or publish it as an artifact) and the same bytes as base64 in `content_base64` (decode and save as an .html file","write_action":false,"price_micros":0,"input_schema":null},{"name":"submit_scaffold_verdicts","description":"Scaffold-mode completion: validate verdicts produced by the calling agent (leaf coverage, verdict vocabulary, mandatory verbatim evidence quotes resolved to spans) and return the stamped assessment TOGETHER WITH the finished, rendered deliverable. `items` is the verdict array from the forced tool call — one object per leaf with `id`, `verdict`, `confidence`, `rationale`, and (for reported/partial)","write_action":true,"price_micros":0,"input_schema":null},{"name":"validate_against_gold","description":"Compute per-leaf agreement between instrument assessments and human gold-standard codings: raw agreement, Cohen's kappa, Gwet's AC1, and binary (reported-vs-rest) sensitivity/specificity with the human coding as the reference standard, plus a span-keyed disagreement list for adjudication. Agreement is reported PER LEAF; the pooled figure is orientation only. Both arguments are arrays of assessment","write_action":false,"price_micros":0,"input_schema":null}],"scan":{"score":82,"grade":"B","scanned_at":"2026-11-01T13:28:14.554Z","report":{"scannerVersion":"0.1.10","scannedAt":"2026-11-01T13:28:14.532Z","components":{"code":{"score":25,"max":25,"notes":["13 source files scanned"]},"reliability":{"score":-1,"max":20,"notes":["no gateway calls yet and no remote to probe"]},"poisoning":{"score":-1,"max":15,"notes":["tools not inspected (local package is not executed); not counted"]},"auth":{"score":12,"max":15,"notes":["local package, no credentials required"]},"maintenance":{"score":12,"max":15,"notes":["last push 71 days ago"]},"identity":{"score":4,"max":10,"notes":["namespace and repository owner differ"]}},"findings":[],"inputs":{"packages":[{"registryType":"pypi","identifier":"target-mcp","version":"0.2.0","found":true,"weeklyDownloads":30,"license":"Apache-2.0","dependencyCount":7,"publishedAt":"2026-08-23T00:07:44.631792Z"}],"repo":{"found":true,"owner":"Black-Swan-Causal-Labs","repo":"target-mcp","archived":false,"pushedAt":"2026-08-23T00:22:52Z","stars":0,"forks":0,"openIssues":0,"ownerType":"Organization","ownerAvatarUrl":"https://avatars.githubusercontent.com/u/281048007?v=4","ownerCreatedAt":"2026-05-01T21:08:07Z","license":"Apache-2.0"},"icon":{"url":"https://blackswancausallabs.com/favicon.png","source":"registry","width":533,"height":300},"presence":{"stars":0,"forks":0,"downloadsWeek":30,"license":"Apache-2.0","lastPushAt":"2026-08-23T00:22:52.000Z","score":17}}}},"grade_history":[{"kind":"downgrade","fromGrade":"A","toGrade":"B","reason":"score 82","createdAt":"2026-11-01T13:28:14.976Z"}],"reviews":[]}