# Ephemeris Time-Series Forecasting (remote · ephemeris.cascade.industries)

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

- Trust score: 91/100 (high trust)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-05

## Components

- remote · `ephemeris.cascade.industries`: 91/100 (this document), [markdown](https://verifymcp.io/servers/industries-cascade-ephemeris/api-mcp.md), [page](https://verifymcp.io/servers/industries-cascade-ephemeris/api-mcp)
- npm · `ephemeris-mcp`: 38/100, [markdown](https://verifymcp.io/servers/industries-cascade-ephemeris/ephemeris-mcp.md), [page](https://verifymcp.io/servers/industries-cascade-ephemeris/ephemeris-mcp)

## Channel facts

- Endpoint: `https://ephemeris.cascade.industries/api/mcp`
- Transports: `streamable-http`
- Auth: `required`
- Version: `1.0.1`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-11-05.

- **Endpoint Security**: 97/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation is enforced on tool calls, advertised via RFC 9728 protected-resource metadata. Discovery is public, which costs nothing: no tool can be invoked without a token.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
  - The authorisation server supports Client ID Metadata Documents, the current MCP client-registration mechanism.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 61/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 2638 tokens (~376/item across 7 items; 7 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 93/100
  - Stability observed for 28 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 7 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 8 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the Ephemeris Time-Series Forecasting MCP server?

Ephemeris Time-Series Forecasting is a hosted endpoint at https://ephemeris.cascade.industries/api/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http industries-cascade-ephemeris 'https://ephemeris.cascade.industries/api/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "industries-cascade-ephemeris": {
      "url": "https://ephemeris.cascade.industries/api/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "industries-cascade-ephemeris": {
      "type": "http",
      "url": "https://ephemeris.cascade.industries/api/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.industries-cascade-ephemeris]
url = "https://ephemeris.cascade.industries/api/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "industries-cascade-ephemeris": {
      "type": "remote",
      "url": "https://ephemeris.cascade.industries/api/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add industries-cascade-ephemeris --url 'https://ephemeris.cascade.industries/api/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  industries-cascade-ephemeris:
    url: "https://ephemeris.cascade.industries/api/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "industries-cascade-ephemeris": {
      "Transport": "http",
      "Url": "https://ephemeris.cascade.industries/api/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add industries-cascade-ephemeris -t streamable-http -u 'https://ephemeris.cascade.industries/api/mcp'
```

### Other

```json
{
  "mcpServers": {
    "industries-cascade-ephemeris": {
      "type": "http",
      "url": "https://ephemeris.cascade.industries/api/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-11-05 (score 91, +1)

No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-11-03 (score 90, +1)

No change was recorded against any check on this day. Stability & Change Management went from 83 to 87. That category is still filling its 30-day observation window: 25 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-31 (score 89, +1)

No change was recorded against any check on this day. Stability & Change Management went from 73 to 77. That category is still filling its 30-day observation window: 22 days of observed history at the previous scan, 23 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-29 (score 88, +1)

No change was recorded against any check on this day. Stability & Change Management went from 67 to 70. That category is still filling its 30-day observation window: 20 days of observed history at the previous scan, 21 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-27 (score 87, +1)

No change was recorded against any check on this day. Stability & Change Management went from 60 to 63. That category is still filling its 30-day observation window: 18 days of observed history at the previous scan, 19 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-25 (score 86, +1)

No change was recorded against any check on this day. Stability & Change Management went from 53 to 57. That category is still filling its 30-day observation window: 16 days of observed history at the previous scan, 17 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-24 (score 85, 0)

- [security] Tool “get_version” rewrote its description, which is the text the model reads

### 2026-10-23 (score 85, +1)

No change was recorded against any check on this day. Stability & Change Management went from 47 to 50. That category is still filling its 30-day observation window: 14 days of observed history at the previous scan, 15 at this one. The score rises as the window fills, whether or not the server changes.

## MCP tools (7)

### `get_version` (~150 tokens)

Inspect the hosted Ephemeris 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), artifact_schema_versions, and runtime_tls (Node release and certificate-trust status; metadata only, no probe connections). 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.

Output parameters:

- `artifact_schema_versions` (object)
- `build_commit`
- `component` (string)
- `runtime_tls` (object)
- `version` (string)

### `describe_forecast` (~332 tokens)

Describe a saved 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/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.

Input parameters:

- `artifact` (object, required): Complete ephemeris.forecast schema_version 1 JSON object returned by forecast or saved by Ephemeris CLI. Pass the object, not a filename, URL, resource URI, request ID, or bearer token. Maximum 1 MiB…
- `series_index` (integer): Zero-based series index; required when the artifact has multiple series, otherwise 0.
- `variate_index` (integer): Zero-based variate index; required for multivariate results, otherwise 0.

### `plot_forecast` (~461 tokens)

Plot a saved 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 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.

Input parameters:

- `artifact` (object, required): Complete ephemeris.forecast schema_version 1 JSON object returned by forecast or saved by Ephemeris CLI. Pass the object, not a filename, URL, resource URI, request ID, or bearer token. Maximum 1 MiB…
- `format` (string): png returns an inline image preview; svg returns an embedded text resource to save as .svg. Neither creates a hosted download URL.
- `history`: Observed points to show: default min(available, max(24, 2*horizon)). all shows full history. View changes never change the artifact or inference.
- `lower` (number): Existing lower quantile. Supply together with upper. Default pairs complementary available levels.
- `series_index` (integer): Zero-based series index; required when the artifact has multiple series, otherwise 0.
- `upper` (number): Existing upper quantile, greater than lower. Supply together with lower.
- `variate_index` (integer): Zero-based variate index; required for multivariate results, otherwise 0.

### `forecast` (~690 tokens)

Forecast a time series

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.

Input parameters:

- `combine` (string): Ensemble only. "mixture" averages the predictive distributions (default); "vincentize" averages the quantiles.
- `context` (object): Local artifact metadata, never sent as model inputs. series aligns with input series; timestamps align with history and future_timestamps with horizon. Units/target/measurement/timezone must come fro…
- `context_len` (integer): Most recent points per variate to feed the model (history length does not affect pricing), 1 to 16384. Defaults to 256. Values beyond the model's context cap are truncated at the cap.
- `horizon` (integer): Number of future steps to forecast, 1 to 4096. Defaults to 64. Some models stop short of this (max_horizon in list_models): route and ensemble skip them, explicit mode rejects the request.
- `idempotency_key` (string): Client-chosen key, 8 to 128 characters of letters, numbers, dot, underscore, colon or hyphen. A retry with the same key and identical API body replays while retained by the server. Retain the key bef…
- `include_artifact` (boolean): Default true: include a portable ephemeris.forecast v1 artifact and embedded JSON attachment (up to 1 MiB), with full input history. Save it client-side for describe_forecast/plot_forecast or the CLI…
- `mode` (string, required): "route": automatically select a model. "ensemble": blend compatible models and may cost more. Neither guarantees accuracy or calibration. "explicit": run the single model named in `model`.
- `model` (string): Required when mode is "explicit". Must be a name returned by list_models.
- `quantiles` (array): Up to 21 quantile levels strictly between 0 and 1, for example [0.1, 0.5, 0.9]. The response keys forecasts by these as decimal strings.
- `series` (array, required): One to 64 series forecast in one request. All share horizon and quantiles.
- `top_k` (integer): Ensemble only: cap on how many models participate.

Output parameters:

- `artifact` (object): Portable ephemeris.forecast v1 JSON including full history and local context. Save client-side and pass the object to describe_forecast/plot_forecast. Not a hosted URL.
- `artifact_error` (string)
- `artifact_status` (string): included or unavailable. A packaging/size failure never discards the paid forecasts/meta response.
- `forecasts` (array): One entry per input series, aligned with the request.
- `meta` (object)

### `list_models` (~96 tokens)

List forecasting 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 in millicredits per series-slot per 64 forecast steps. History length has no billing multiplier. Call this before using forecast in explicit mode; the deployed panel can differ from any documentation.

Output parameters:

- `models` (array)

### `get_balance` (~41 tokens)

Get credit balance

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

Output parameters:

- `active_holds_mc` (string): Millicredits reserved by in-flight forecasts.
- `balance_mc` (string): Spendable millicredits (ledger minus active holds).

### `get_usage` (~86 tokens)

Get recent 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.

Input parameters:

- `limit` (integer): Rows per page, 1 to 200. Defaults to 50.
- `offset` (integer): Rows to skip. Use `pagination.next_offset` from the previous page.

Output parameters:

- `data` (array): Request log rows, newest first.
- `limit` (number)
- `offset` (number)
- `pagination` (object)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/industries-cascade-ephemeris/api-mcp#diagnostics

## Score history

- 2026-11-05: 91
- 2026-11-04: 90
- 2026-11-03: 90
- 2026-11-02: 89
- 2026-11-01: 89
- 2026-10-31: 89
- 2026-10-30: 88
- 2026-10-29: 88
- 2026-10-28: 87
- 2026-10-27: 87
- 2026-10-26: 86
- 2026-10-25: 86
- 2026-10-24: 85
- 2026-10-23: 85
- 2026-10-22: 84
- 2026-10-21: 84
- 2026-10-20: 83
- 2026-10-19: 83
- 2026-10-18: 82
- 2026-10-17: 82
- 2026-10-16: 82
- 2026-10-15: 81
- 2026-10-14: 81
- 2026-10-13: 80
- 2026-10-12: 80
- 2026-10-11: 79
- 2026-10-10: 76
- 2026-10-07: 36

## Common questions

### What is the Ephemeris Time-Series Forecasting MCP server?

Ephemeris Time-Series Forecasting is an MCP server listed in the public MCP registry as industries.cascade/ephemeris. Probabilistic time-series forecasts from zero-shot foundation models: routed, single or ensembled. This page covers its hosted endpoint (https://ephemeris.cascade.industries/api/mcp).

### Is the Ephemeris Time-Series Forecasting MCP server safe to use?

Ephemeris Time-Series Forecasting scores 91 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the Ephemeris Time-Series Forecasting MCP server expose?

Ephemeris Time-Series Forecasting exposes 7 tools: get_version, describe_forecast, plot_forecast, forecast, list_models, and 2 more. Their descriptions and schemas cost roughly 1,856 tokens of context every time the server is loaded.

### Does the Ephemeris Time-Series Forecasting MCP server require authentication?

Yes. Ephemeris Time-Series Forecasting asked us for credentials when we connected, so you will need to authorise it in your MCP client before it can do anything.

### Is the Ephemeris Time-Series Forecasting MCP server still maintained?

Ephemeris Time-Series Forecasting is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What did VerifyMCP test on the Ephemeris Time-Series Forecasting MCP server?

VerifyMCP ran 13 checks on Ephemeris Time-Series Forecasting, covering TLS certificate, Authorization, HTTPS, HSTS header and 9 more. Supply Chain Security and Provenance & Transparency do not apply to a hosted endpoint, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.

## Links

- Remote endpoint: https://ephemeris.cascade.industries/api/mcp
- Authorisation metadata: https://ephemeris.cascade.industries/.well-known/oauth-protected-resource/api/mcp
- Repository: https://github.com/TensorLink-AI/ephemeris-mcp
- Website: https://ephemeris.cascade.industries/
- Changelog RSS feed: https://verifymcp.io/servers/industries-cascade-ephemeris/api-mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/industries-cascade-ephemeris/api-mcp/changelog.json
- Trust report (JSON): https://verifymcp.io/servers/industries-cascade-ephemeris/api-mcp.json
- HTML version of this page: https://verifymcp.io/servers/industries-cascade-ephemeris/api-mcp