Ephemeris Time-Series Forecasting MCP server

• describe_forecastFree

  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 unknown. Sum of medians only for period_total; it is not a cumulative-distribution interval or median. No calibrated coverage, causal explanation, path/peak probability, or business action is inferred. Example: pass {artifact: <forecast result artifact>}; choose series_index/variate_index for multiple results. Maximum 1 MiB; malformed/version/shape errors are recoverable by fixing the artifact or using CLI, never rerunning inference. Missing labels may be corrected in a COPY of context without changing request/response. No filesystem access, URL fetches, persistent storage, Gnomon import, or scoring.

• forecastwrite actionFree

  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_forecast/plot_forecast. Save the embedded JSON attachment: it includes full input history and local context; no hosted storage is created. Context never becomes a model input. Billing is at meta.billing in millicredit strings (100 mc = 0.1 credits). Missing future inputs mean not supplied, not no events. Quantile bands do not establish coverage, cumulative intervals or peak probabilities. After uncertain completion, reuse the same key and API request; an expired key may cause a new charge.

• get_balanceFree

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

• get_usageFree

  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.

• get_versionFree

  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 schema versions are independent; this tool cannot inspect local installations, check the latest registry release or establish model quality. Use list_models for live model capabilities. After a connection failure reconnect and retry; no forecast could have been submitted by this tool.

• list_modelsFree

  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 documentation.

• plot_forecastFree

  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. Default history view is most recent max(24, 2*horizon) points, capped by available history; history: all shows all. Dates only when supported by recorded metadata, otherwise sampling steps. Bands do not establish calibrated coverage; missing/crossed points are omitted and counted. Maximum 1 MiB input. Select series_index/variate_index for multiple results. Fix argument/shape errors without rerunning inference. User-supplied labels can be corrected in a COPY of artifact context offline; no new forecast needed. Client decides preview/download UI. URNs identify attached bytes, not hosted URLs; no filesystem access, URL fetching or persistent storage.

• Code scan2 source files scanned25/25
• Live reliabilityremote reachable in 1807ms20/20
• Tool poisoning7 tool descriptions checked15/15
• Auth qualityAPI key sent as a header8/15
• Maintenancelast push 4 days ago15/15
• Maintainer identitynamespace and repository owner differ; GitHub account older than a year; website matches verified namespace8/10

Safety score

91/100

higher than 85% of 48,255 servers

Tools

7

the typical server has 7

Tools that change things

14%

typical: 0%. Fewer write tools means less an agent can break

Uptime

100%

of our recent checks; the typical remote server answers 100%

Response time

1,104 ms

faster than 9% of 30,031 servers

Downloads a week

431

more than 86% of 12,191 servers with a package

Ephemeris Time-Series Forecasting: common questions

Is Ephemeris Time-Series Forecasting MCP server safe?

Yes, by our scan: it is graded A (91/100). Read the Ephemeris Time-Series Forecasting safety report

How do I install Ephemeris Time-Series Forecasting?

It runs remotely at ephemeris.cascade.industries. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.

Does Ephemeris Time-Series Forecasting need an API key?

Yes. The registry entry asks for EPHEMERIS_API_KEY, Authorization.

Is Ephemeris Time-Series Forecasting maintained?

The last commit was 25 days ago (2026-10-10). The latest release is v1.0.1.

Is Ephemeris Time-Series Forecasting up?

100% of our last 28 checks got an answer. We check remote servers about four times a day.

How does Ephemeris Time-Series Forecasting compare with other MCP servers?

safety score 91/100 (higher than 85% of 48,255 servers); tools 7 (the typical server has 7); tools that change things 14% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.