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Ephemeris Time-Series Forecasting

REMOTE · EPHEMERIS.CASCADE.INDUSTRIES · 2 COMPONENTS

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

+3 this week 91 Trust /100

Last scanned (20 hours ago)

Scores higher than 98% of remote servers

Reachable. Last reached 5 Nov 2026.

Category AI and Machine Learning

Trust breakdown (7 categories)

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. How we score → Why this is hard to score →

Endpoint Security97
Transport & Reachability100
Schema Quality & AI Usability61
  • AI-judged instruction clarity (excellent).Pass
  • 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. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management93
  • Stability observed for 28 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
  • Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 7 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 8 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
What we tested

Checks we ran (13)

  • TLS certificate
  • Authorization
  • HTTPS
  • HSTS header
  • DNSSEC
  • Transport
  • Schema quality
  • Stability
  • Tool coverage
  • Injection markers
  • Destructive annotations
  • Judged manipulation
  • MCP protocol

Does not apply to this hosted endpoint (2)

  • Supply Chain SecurityScored on package channels only. This is a hosted endpoint, so there is nothing to install or inspect.
  • Provenance & TransparencyScored on package channels only. This is a hosted endpoint, so there is nothing to install or inspect.

The score does not measure everything. What the score does not measure →

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 5 Nov 26 +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.

  • 3 Nov 26 +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.

  • 31 Oct 26 +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.

  • 29 Oct 26 +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.

  • 27 Oct 26 +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.

  • 25 Oct 26 +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.

  • 24 Oct 26 0
    • Tool “get_version” rewrote its description, which is the text the model reads security
  • 23 Oct 26 +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.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 5 Nov 2026 · Probed https://ephemeris.cascade.industries/api/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=ephemeris.cascade.industries CN=YR1,O=Let's Encrypt,C=US 10 Sept 2026 9 Dec 2026 RSA 2048 SHA256-RSA 61b87ddd88f5818aa9cba043b871fc8d7d8
SANs: ephemeris.cascade.industries
CN=YR1,O=Let's Encrypt,C=US (CA) CN=Root YR,O=ISRG,C=US 3 Sept 2025 2 Sept 2028 RSA 2048 SHA256-RSA a20253f15f2691c05dc1ce13b9bcca4e
CN=Root YR,O=ISRG,C=US (CA) CN=ISRG Root X1,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 RSA 4096 SHA256-RSA f24b6d17f9d9ad7cb1c9fea78782699f

Background: What to check on a remote MCP endpoint →

DNSSEC insecure

Validation of ephemeris.cascade.industries. — Not signed

Zone DS Keys Algorithms Outcome
. Trust anchor 20326, 38696 8, 8 Verified
industries. DS published 9211, 47486 8, 8 Verified
cascade.industries. No DS Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation
Authentication Enforced and verified

The endpoint asked for a token and published valid RFC 9728 metadata describing how to get one.

Result Enforced and verified
Enforced On tool calls
HTTP status 200

WWW-Authenticate challenge Bearer realm="ephemeris", error="invalid_token", error_description="Sign in to Ephemeris: your MCP client can open the sign-in page for you, or send Authorization: Bearer pc_live_... No account yet? Create a free one at https://ephemeris.cascade.industries/sign-up (new accounts get a small free credit).", resource_metadata="https://ephemeris.cascade.industries/.well-known/oauth-protected-resource/api/mcp"

Bearer realm="ephemeris", error="invalid_token", error_description="Sign in to Ephemeris: your MCP client can open the sign-in page for you, or send Authorization: Bearer pc_live_... No account yet? Create a free one at https://ephemeris.cascade.industries/sign-up (new accounts get a small free credit).", resource_metadata="https://ephemeris.cascade.industries/.well-known/oauth-protected-resource/api/mcp"
Header Value
strict-transport-security max-age=63072000

Protected resource metadata

Document https://ephemeris.cascade.industries/.well-known/oauth-protected-resource/api/mcp
Retrieved Yes
Resource https://ephemeris.cascade.industries/api/mcp
Authorisation server https://clerk.ephemeris.cascade.industries

Background: How OAuth 2.1 works in the 2026 MCP spec →

Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://ephemeris.cascade.industries/api/mcp Verified 200
http (plaintext) http://ephemeris.cascade.industries/api/mcp HTTPS enforced 308 https://ephemeris.cascade.industries/api/mcp
MCP tools · 7 exposed · ~1,856 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
describe_forecast ~332

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.

NameTypeReqDescription
artifactobjectyesComplete 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_indexinteger–Zero-based series index; required when the artifact has multiple series, otherwise 0.
variate_indexinteger–Zero-based variate index; required for multivariate results, otherwise 0.

Structured output declared, but exposes no named fields.

No examples provided.

forecast ~690

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.

NameTypeReqDescription
combinestring–Ensemble only. "mixture" averages the predictive distributions (default); "vincentize" averages the quantiles.
contextobject–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_leninteger–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.
horizoninteger–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_keystring–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_artifactboolean–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…
modestringyes"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`.
modelstring–Required when mode is "explicit". Must be a name returned by list_models.
quantilesarray–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.
seriesarrayyesOne to 64 series forecast in one request. All share horizon and quantiles.
top_kinteger–Ensemble only: cap on how many models participate.
NameTypeReqDescription
artifactobject–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_errorstring––
artifact_statusstring–included or unavailable. A packaging/size failure never discards the paid forecasts/meta response.
forecastsarray–One entry per input series, aligned with the request.
metaobject––

No examples provided.

get_balance ~41

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

Input schema present but exposes no named parameters.

NameTypeReqDescription
active_holds_mcstring–Millicredits reserved by in-flight forecasts.
balance_mcstring–Spendable millicredits (ledger minus active holds).

No examples provided.

get_usage ~86

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.

NameTypeReqDescription
limitinteger–Rows per page, 1 to 200. Defaults to 50.
offsetinteger–Rows to skip. Use `pagination.next_offset` from the previous page.
NameTypeReqDescription
dataarray–Request log rows, newest first.
limitnumber––
offsetnumber––
paginationobject––

No examples provided.

get_version ~150

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.

Input schema present but exposes no named parameters.

NameTypeReqDescription
artifact_schema_versionsobjectyes–
build_commit–yes–
componentstringyes–
runtime_tlsobjectyes–
versionstringyes–

No examples provided.

list_models ~96

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.

Input schema present but exposes no named parameters.

NameTypeReqDescription
modelsarray––

No examples provided.

plot_forecast ~461

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.

NameTypeReqDescription
artifactobjectyesComplete 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…
formatstring–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.
lowernumber–Existing lower quantile. Supply together with upper. Default pairs complementary available levels.
series_indexinteger–Zero-based series index; required when the artifact has multiple series, otherwise 0.
uppernumber–Existing upper quantile, greater than lower. Supply together with lower.
variate_indexinteger–Zero-based variate index; required for multivariate results, otherwise 0.

Structured output declared, but exposes no named fields.

No examples provided.

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.

remote · ephemeris.cascade.industries

# add to Claude Code
claude mcp add --transport http industries-cascade-ephemeris 'https://ephemeris.cascade.industries/api/mcp'
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.