Modelmeter

xyz.modelmeter由 modelmeter.xyz 發布官方發布者v1.0.0更新於 Oct 24, 2026

The changelog of record for the AI stack: sunset checks, deprecations, pricing, and model events.

已驗證Streamable HTTP可網頁執行資料與分析AI 與機器學習

概覽

AI 產生的概覽

遠端 MCP 伺服器,提供經核驗的 LLM 模型價格、淘汰與變更事件紀錄,並可估算 token 呼叫成本。

可以做什麼
  • 列出模型,並讀取包含正規化價格、能力與價格歷史摘要的模型卡片
  • 依 token 數量估算 LLM API 呼叫的美元成本,含轉售商相對上游的加價
  • 取得某個模型或供應商的歷史價格時間序列
  • 瀏覽淘汰、價格變動、發布與市場事件的變更日誌,可依嚴重程度篩選
  • 檢查一組模型 ID 的預定退役時間、剩餘天數與遷移目標
  • 列出依關閉日期排序的各模型退役紀錄
適用情境
當助理需要目前或歷史 LLM 價格、估算 API 呼叫成本,或在推薦、遷移模型前確認所用模型是否已淘汰、即將停用或已退役時適用。
執行需求
需要遠端 Streamable HTTP 端點;無需驗證、安裝或 API 金鑰。用戶端需支援透過 HTTP 連線遠端 MCP 伺服器。
安裝前請注意
僅做唯讀查詢,不寫入或修改資料。價格與事件資料來自第三方,雖標示為經人工核驗,成本估算仍應視為參考資訊而非帳單級資料。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Modelmeter,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/xyz.modelmeter%2Fmodelmeter/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "modelmeter": {
      "type": "http",
      "url": "https://modelmeter.xyz/mcp"
    }
  }
}

README

Modelmeter

The changelog of record for the AI stack. Live at modelmeter.xyz.

What this is

A machine-readable, source-verified record of everything that changes in the model layer: deprecations with sunset dates and migration targets, silent model swaps behind stable IDs, price changes, releases — plus three years of pricing history and cost tooling. Every event carries its sources with verbatim quotes (most with archive snapshots), a verification status (unverified → human-reviewed verified), and corrections are never silent — a correction event points at what it supersedes.

Built primarily for AI agents to call programmatically, secondarily for humans through a dashboard. Reach it three ways: plain GET URLs returning JSON, a remote MCP server any tool-calling agent can connect to, and a visual dashboard built on the same endpoints. The wedge: clean URLs, stable JSON contracts, an OpenAPI spec, and an llms.txt discoverability file. Most sites in this space are JS-heavy SPAs that agents can't use; Modelmeter is built the other way around.

Endpoints

  • GET /estimate?model=X&input=N&output=M — token cost for a hypothetical call, including upstream-markup comparison for reseller models
  • GET /models — current model catalog, with filters
  • GET /model?id=X — unified card for one model: normalized pricing, capabilities (context window, vision, reasoning, tags), availability, reseller markup, and a price-history summary (launch vs. current price, % change, all-time low/high)
  • GET /check?models=gpt-4o,claude-sonnet-4-6 — is my stack okay? Verdict per model: scheduled retirements with days-remaining and migration targets, past retirements, breaking changes, or a clean bill
  • GET /deprecations — per-model retirement rows: which model dies when, with runway and migration target
  • GET /feed.xml / GET /feed.json — RSS 2.0 / JSON Feed 1.1 of breaking and action-required events
  • GET /events — the changelog of record: deprecations, price changes, launches and surrounding market events, each with severity (breaking | action_required | informational), announced_at/effective_at dates, sources with quotes, and verification status. Filters: provider, type, model, severity, since, until, status
  • GET /history — historical pricing time-series per model, with filters
  • GET /pricing.json — raw pricing snapshot
  • GET /events.json — raw events snapshot
  • GET /history.json — raw historical time-series

See public/openapi.yaml for the full spec.

GitHub Action

Fail CI when a model your repo depends on is deprecated, sunsetting, or already retired:

yaml
- uses: modelmeters/modelmeter/actions/check@main  # with:  #   models: "gpt-4o, claude-sonnet-4-6"   # optional — otherwise the repo is scanned for known model ids  #   fail-on: breaking                      # breaking (default) | retired | none  #   warn-days: "120"                       # sunsets within N days fail; beyond N warn

The action scans your repo for known model ids (catalog + every model named in a deprecation event, dashed and dotted spellings), calls /check, annotates the exact file:line of each affected model, writes a job-summary table with migration targets, and exits nonzero per your fail-on policy.

MCP server

Modelmeter is also a remote MCP server, so any tool-calling agent (Claude, Hermes, …) can call it natively over the Streamable HTTP transport — no auth, no install:

https://modelmeter.xyz/mcp

Tools: check_model_dependencies, list_deprecations, estimate_cost, get_model, list_models, get_price_history, list_events. Start with list_models to discover ids, then get_model or estimate_cost. The MCP tools return the same data as the REST endpoints above — use whichever your runtime prefers.

Datasets

  • pricing/ — current and historical model pricing across providers
  • events/ — the events record (schema 2.0.0): deprecations, price changes, releases, and market events with primary-source citations, verbatim quotes, and verification status

Each entry carries a last_verified date. Daily snapshots in pricing/snapshots/ accumulate the historical record. Wrong pricing is the existential risk — the schema requires explicit human verification before an entry is served.

Contributing

Found a price change? Open a PR updating pricing/current.json with the new value, an updated last_verified date, and the source URL.

Spotted a meaningful AI market event? Add an entry to events/current.json with primary-source citations and verified: true.

Automation opens issues when provider pricing pages change. Pick one up if you want to help.

License

MIT — see LICENSE.

來源:README.md,提交 5c026a1

工具

7

estimate_cost

Estimate the USD cost of an LLM API call for a given model and token counts. Returns input/output/total cost, plus reseller markup vs. the upstream model when applicable.

輸入參數model必填input_tokens必填output_tokens必填

get_model

Unified card for one model in a single call: normalized pricing, capabilities (context window, vision, reasoning, tags), availability, reseller markup vs. upstream, and a price-history summary (launch vs. current price, percent change, last change date, all-time low/high).

輸入參數id必填

list_models

List available models with their current pricing. Optionally filter by provider.

輸入參數limitproviderinclude_unavailable

get_price_history

Historical pricing time-series for a model or provider. Each point is a dated snapshot of the per-Mtok rates.

輸入參數modelsinceuntilprovider

list_events

The changelog of record for the model layer: deprecations, price changes, launches, and the market events around them. Filter by severity to find what demands action: 'breaking' (model going away, ID changing), 'action_required' (price/rate-limit/context changes), 'informational' (releases, funding).

輸入參數typelimitsinceuntilstatusproviderseverity

check_model_dependencies

Is my stack okay? Check a list of model ids against the record: scheduled retirements with days-remaining countdowns and migration targets, past retirements, and other breaking/action-required changes. Id matching tolerates dots vs dashes, dated snapshot suffixes, and bare or provider-prefixed forms. Call this at startup or in CI with the models you depend on.

輸入參數models必填

list_deprecations

Per-model retirement rows from the record: which model dies when, with runway and migration target. Default shows scheduled (upcoming) retirements sorted by shutdown date.

輸入參數limitstatusprovider

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

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