Connect-MCP

Ephemeris Time-Series Forecasting

industries.cascade/ephemeris · v1.0.1

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

MCPremotelocal · npmAPI keyWeatherAI & LLM

Reported outcomes

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Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 7 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

B 84/100

What it does: 7 tools · 6 read, 1 write · Weather, AI & LLM, Files & storage

Test call list_models: needs a key: HTTP 401 (1,012 ms)

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +6
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +10
  • Read/write annotations: +5
  • Safe test call: +8
  • 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://ephemeris.cascade.industries/api/mcp
Package
registry:   npm
identifier: ephemeris-mcp
version:    1.0.0
transport:  stdio

Tools

7 tools listed at last check
  • get_version 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)
  • describe_forecast 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/ch
  • plot_forecast 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 inv
  • 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, quanti
  • list_models 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
  • get_balance Return the account's spendable credit balance in millicredits, excluding credits reserved by in-progress forecasts. 1000 millicredits equal one credit.
  • get_usage 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.

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