AI model releases, price changes and deprecations in one feed: chat, embedding, speech, video.
Scored across 8 tools
Each tool targets a distinct question: single-model lookup, criteria search, side-by-side comparison, replacement finding, cost estimation, price history, change feed, and daily digest. The only near-overlap (get_today vs list_model_changes) is explicitly disambiguated by one being a curated summary and the other a paginated raw feed.
All tool names follow a verb_noun snake_case pattern with clear verbs like get, search, compare, estimate, find, and list. The one slightly idiomatic name, get_today, still reads as a get operation and does not break the overall consistency.
Eight tools is well-scoped for a model intelligence server; each tool addresses a distinct workflow and none feels redundant. The count is neither too thin nor too heavy for the stated purpose.
The tool surface covers the full set of model-information needs: discovery, detail, comparison, cost estimation, price history, change tracking, daily summaries, and replacement recommendations. There are no obvious dead ends; an agent can move from an unknown need to a specific model to cost and replacement decisions.
Put two or more models side by side: price, context, benchmark scores per subject, and what each costs per month at a given volume. Use this instead of calling get_model repeatedly: it aligns the fields and marks which subjects a model has not been tested on, so a missing score is not read as a low one.
Inputs: ids (required), monthlyMillionTokens.
What one model costs per month at a given token volume, in USD and KRW. Token prices are per million and hard to reason about directly; this turns them into a monthly bill. Input and output are mixed 75/25 unless you pass your own split.
Inputs: id (required), inputShare, monthlyMillionTokens.
What to switch to when a model is gone or you need a fallback. Ranked by closeness in measured performance, not by vendor or price: what you usually need to preserve first is the quality of the output. Candidates whose context window is less than half the original are excluded. Returns the score, price and context deltas so you can judge; we do not pick for you.
Inputs: id (required).
Pricing, context length and catalog status for one model. Accepts an OpenRouter id (anthropic/claude-opus-5) or a Hugging Face repo id.
Inputs: id (required).
Price history for one model: when the price changed and to what. The public catalog only exposes the current price, so this answers 'was this cheaper last month?'. Each entry holds until the next one. History starts when AI Wave began recording, not when the model launched.
Inputs: id (required).
Today in one call: the top 5 models, which ones climbed, whose pricing changed in the last 24h, and what was newly listed in the last 7 days. Use this instead of paging list_model_changes and re-deriving the summary: price changes are already collapsed to one per model, with the raw count kept.
Inputs: no named parameters.
Changes across AI models: new releases, price changes, API changes and deprecations. Normalized from vendor release notes, Hugging Face, the OpenRouter catalog, GitHub and the LiteLLM price map, deduplicated per model, each marked official or pending review. Poll with since (unix seconds) and feed the returned latest back next time.
Inputs: type, limit, model, since.
Shortlist models by budget, context and capability, ranked by measured performance. Use this to answer 'which model should I use for X': it returns benchmark scores alongside price so the trade-off is visible in one call. Sort by a subject (math, coding, science, reading) to find a model good at one thing.
Inputs: mode, limit, sortBy, vendor, +5 more.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Read-only AI news with sources, Model Tracker prices, releases and retirement dates.
AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.
AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.
The changelog of record for the AI stack: sunset checks, deprecations, pricing, and model events.
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