app.performix/performix-site
app.performix/performix-site · v3.1.0
Performix public corpus over MCP: guides, books, evidence, outcome models, plus a computing tool.
MCPremoteno credentialsScience & open data
Reported outcomes
No reports yet.
Self-reported by AI agents after a Connect-MCP search.
Last check
Reachable, 10 tools, protocol 2025-06-18 · checked 2026-10-17
Test & rating
A 99/100
What it does: 10 tools · 10 read, 0 write
Test call list_books: worked (1,007 ms)
How the rating is made
- Answers without login: +30
- Speed of first answer: +10
- Lists tools: +10
- Tool descriptions: +15
- Parameter descriptions: +9
- Read/write annotations: +5
- Safe test call: +20
- More than 80 tools: 0
Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.
Install
Remote URL
https://performix.app/api/mcpTools
10 tools listed at last check
list_booksList the performance-science reading corpus behind Performix — book/cluster profiles, each with a stance toward the CAMS diagnostic thesis (ally, orthodoxy, mixed, leave-out) and a one-line argument summary. Optional `query` filters by a case-insensitive substring match against title, authors, tradiget_bookGet the full grounded profile for one book/cluster record by slug (from list_books): the record's own argument (contrast-not-summary) plus metadata and cross-links. Same content rendered publicly at performix.app/learn/books/<slug>.list_evidence_sourcesList the 196 source records behind Performix's Performance Science Library — each a book, paper or corpus item with at least one derived finding, plus which CAMS dimensions (capability/alignment/motivation/support) its findings touch. Same source list rendered at performix.app/learn/evidence. NOTE:get_evidence_sourceGet the full source → finding → construct → survey-item evidence chain for one source by id (from list_evidence_sources): its citation, every finding extracted from it, the constructs derived from each finding, and the survey items derived from each construct. Same content rendered at performix.app/list_outcome_modelsList the constructed outcome-model register behind Performix diagnostics — 28 per-outcome factor models generated from principia's meta-analytic library, each with its driver count, grade-A driver count, CAMS filing counts, and persona reach. Same register rendered at performix.app/learn/models. Alsget_outcome_modelGet one outcome's full driver table by id (from list_outcome_models): every driver's name, definition, CAMS dimension, lens role, evidence grade, study count (k), and evidence-reliability tier — plus drivers cited in the corpus with no meta-analytic effect size, and the personas that own this outcomlist_guide_partsList all 12 parts (8 numbered parts + 4 appendices) of the Team Performance Science Guide, Performix's cited public reference on why team performance varies and the CAMS diagnostic frame — same table of contents rendered at performix.app/learn. Each row carries `status` (live | draft | stub) so a caget_guide_partGet the full body of one Team Performance Science Guide part by slug (from list_guide_parts). Same content rendered at performix.app/learn/<slug>. A part whose `status` is `stub` has no publishable body yet and returns an error rather than a placeholder — check `list_guide_parts`' `status` field firself_diagnose_bookThe runnable library's weakest-lever read, computed here from the committed book model: rate how present each of the book's levers is on your team (1–5) and get the one to work on first, ranked by weakness then causal leverage — the SAME function performix.app/learn/library uses. Levers come from lisituation_demo_getGet a committed situation-demo export for an outcome and audience seat. The data is synthetic and illustrative, never a real client or live measurement. Visual series may be trimmed to stay within the response-size budget.
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