Self-hosted forecasting + prediction service. Five zero-shot time-series foundation models (Chronos-2, TimesFM 2.5, Moirai-2, Toto-1, Sundial) across six forecast types, plus nine supervised tabular ML backends (LightGBM, XGBoost, sklearn family) with calibrated / stacking / diversified meta-learners. Unified REST API + MCP server.
Insufficient evidence to grade. This server's source has not been statically analyzed, so a low grade would only mean "nothing found", not "nothing there". We don't show a reassuring grade we can't stand behind. Attested signals (CVEs, provenance) below still apply.
Once the source is analyzed (see the analysis flag in the header), a graded score appears here. How analysis works: methodology.
graded 12m ago · see ecosystem CVEs →
no known CVEs for this server.
No tool-safety findings — heuristic detectors run on the compute-risk cadence; a finding appears when a tool trips a rule.
[](https://mcpobservatory.com/servers/github:psyb0t/docker-predictalot/security) Heuristic, inferred signals — false positives (legitimately powerful tools, forks, language ports) are expected. Treat each as "review this", not a verdict. See the ecosystem-wide picture on the security hub, or the fleet security of psyb0t.