Ephemeris Time-Series Forecasting

industries.cascade/ephemeris

Probabilistic time-series forecasts from zero-shot foundation models: routed, single or ensembled.

Yes, your AI can use this right now.Answered a live MCP handshake in 1445 ms with no sign-in needed and exposes 7 tools.

Connect it

Settings → Connectors → Add custom connector
URL: https://ephemeris.cascade.industries/api/mcp

7 tools, verified live

Pulled straight from the server with tools/list on 2026-10-17.
get_versionread-only

Read this deployed MCP server's version, nullable build commit and supported saved forecast schema versions. Call with {}. No API key, account access, inference, charges or writes; network access to this server only. Returns component, version, build_commit (full source SHA or null when unavailable), and artifact_schema_versions. Unknown commit stays null. Server, CLI, npm bridge and artifact sche

describe_forecastread-only

Deterministic calculations from a complete ephemeris.forecast v1 artifact object, including CLI artifacts. No inference or forecast charge; this hosted tool still receives data over the network. Returns scope, result, basis, limitations and source pointers: last-observed baseline, median endpoint/change, marginal-median aggregates, and exact saved billing units. Missing medians/context remain unkn

plot_forecastread-only

Render a complete ephemeris.forecast v1 artifact object as PNG (default inline preview) or SVG (embedded resource to save). No inference or forecast charge; hosted processing receives the artifact over the network. Example: {artifact: <saved artifact>, format: png}. Requires returned q0.5; never invents a median. Observed history, forecast boundary, median and nominal quantile bands are labeled. D

forecast

Submit numeric observations to forecast future sampling steps. Spends credits on successful calls. Choose and retain idempotency_key before submitting; no automatic retries, replay depends on server retention. Minimal example: {mode: route, series: [{values: [10,12,11], freq: D}], horizon: 2, quantiles: [0.1,0.5,0.9]}. Returns forecasts and meta as before, plus artifact by default for describe_for

list_modelsread-only

Discover the model panel: each model's availability right now (healthy), capabilities (multivariate, covariates, max_horizon, auto_max_horizon), its weight in an ensemble at each horizon, pinned and actually served weight revision, price per thousand series-slots in millicredits and maximum billable context. Call this before using forecast in explicit mode; the deployed panel can differ from any d

get_balanceread-only

Return the account's spendable credit balance in millicredits, excluding credits reserved by in-progress forecasts. 1000 millicredits equal one credit.

get_usageread-only

Return the account's forecast request log, newest first, with the mode, models used, series count, horizon, credits estimated and settled, HTTP status and latency of each request.

Alternatives in AI & Agents

Compare →
Try “Notion”, “Stripe”, “create invoice”, “browser”