Modelmeter

xyz.modelmeter由 modelmeter.xyz 发布官方发布者v1.0.0更新于 Oct 24, 2026

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

已验证Streamable HTTP可网页运行数据与分析AI 与机器学习

概览

AI 生成的概览

远程 MCP 服务器,提供经核验的 LLM 模型价格、弃用与变更事件记录,并可估算 token 调用成本。

可以做什么
  • 列出模型,并读取包含归一化价格、能力与价格历史摘要的模型卡片
  • 按 token 数量估算 LLM API 调用的美元成本,含转售商相对上游的加价
  • 获取某个模型或供应商的历史价格时间序列
  • 浏览弃用、价格变动、发布与市场事件的变更日志,可按严重程度筛选
  • 检查一组模型 ID 的计划退役时间、剩余天数与迁移目标
  • 列出按关停日期排序的各模型退役记录
适用场景
当助手需要当前或历史 LLM 价格、估算 API 调用成本,或在推荐、迁移模型前确认所用模型是否已弃用、即将停用或已退役时适用。
运行要求
需要远程 Streamable HTTP 端点;无需认证、安装或 API 密钥。客户端需支持通过 HTTP 连接远程 MCP 服务器。
安装前请注意
仅做只读查询,不写入或修改数据。价格与事件数据来自第三方,虽标注为经人工核验,成本估算仍应视为参考信息而非账单级数据。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Modelmeter,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/xyz.modelmeter%2Fmodelmeter/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "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.

来源: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.

输入参数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).

输入参数id必填

list_models

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

输入参数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.

输入参数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).

输入参数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.

输入参数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.

输入参数limitstatusprovider

版本历史

1
  1. v1.0.0最新Sep 16, 2026

评分

已满足适用检查项的 100%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通必需25 分
  • 已声明认证方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分