原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Compute Finance Oracle

作者:compute-finance版本 0.12.2i★ –i在你的电脑上运行
注册名称io.github.compute-finance/mcp

安装

概览

作者提供的说明(英文原文)

Live AI compute pricing oracle — real-time LLM model prices across providers

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 会计、财务与税务

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "compute-finance": {
      "command": "npx",
      "args": [
        "-y",
        "@compute-finance/mcp",
        "setup"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add compute-finance -- npx -y @compute-finance/mcp setup

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "compute-finance": {
      "command": "npx",
      "args": [
        "-y",
        "@compute-finance/mcp",
        "setup"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "compute-finance": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@compute-finance/mcp",
        "setup"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 compute-finance 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“会计、财务与税务”中的其他服务器比较i

  • 星标数多于此分类中其他 1735 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1735 个服务器的 80% 更新
  • 基础检查结果等于或优于此分类中其他 1735 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Compute Finance Oracle 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.12.2)于9天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Finance Toolkit, SolidInvoice, Korea Tax Calculator

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Finance Toolkit

作者:JerBouma

500+ transparent financial methods calculated from raw statements, not third-party endpoints.

电脑或云端★ 5,496MIT昨天更新
安装

SolidInvoice

作者:SolidInvoice

Create and send invoices and quotes, manage clients, and track payments in SolidInvoice.

在云端运行★ 981MIT8天前更新
安装

Korea Tax Calculator

作者:UpstageAI

Korean tax calculation and tax-audit judgment MCP: 96 tools with statutory citations.

在你的电脑上运行★ 97MIT昨天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

@compute-finance/mcp

Live AI compute pricing oracle — real-time LLM model prices across nine vendors (Anthropic, OpenAI, Google, DeepSeek, xAI and four more) via the Compute Finance Oracle.

A stdio MCP server. Works in any MCP client. Includes optional Claude Code skills for session cost analysis.

Quick start

Claude Code (recommended)
npx @compute-finance/mcp setup

This single command:

  1. Registers the MCP server at user scope (claude mcp add)
  2. Installs Claude Code skills (/cf-session-management, /cf-session-consumption, /cf-active-sessions, /cf-account)
  3. Installs the cost hook — a UserPromptSubmit hook that injects session cost into Claude's context so every response can show how much you've spent

Restart Claude Code after setup.

To also answer for your own Compute Finance account, connect it once — see Your account.

Or register manually without skills/hook:

claude mcp add --scope user compute-finance -- npx @compute-finance/mcp
Cursor / VS Code / Any MCP client

Add to your MCP config (.cursor/mcp.json, VS Code settings, etc.):

{

"mcpServers": { "compute-finance": { "command": "npx", "args": ["@compute-finance/mcp"] } } }

From source
git clone https://github.com/compute-finance/mcp.git

cd mcp npm install && npm run build npx . setup

Tools

Tools are named by layer prefix and come in three groups. The public and local groups need no API key and no account.

GroupPrefixesWhat the tools touch
Public datadata_get_*, compute_*Read the live Compute Finance Oracle over unauthenticated GETs
Local sessionsrender_*, analyze_*, telemetry_get_*Read Claude Code transcripts on this machine, price them at live oracle rates, and append the measurements to the session logs under ~/.compute-finance/, which telemetry_get_history reads back; nothing is uploaded
Your accountaccount_*Registered only once an app grant is connected, and only the tools that grant allows. With Read access they read the account's balance, spend, keys and history; with Act access some of them act on the account — create an API key, freeze or unfreeze a key, set budget caps, configure auto top-up

The account_* tools are not listed below: the exchange publishes them, and this package copies none of them. See Your account.

Data (live oracle)
ToolDescription
data_get_basketEvery model in the current SCU index, with provider, family (e.g. openai.gpt, anthropic.claude), base_* and billed_* USD prices per million tokens, per-component cache pricing (read, write-5m, write-1h), a reasoning output price and the long-context price ladder
data_get_pricePrice for a single model (e.g. anthropic/claude-opus-4.8) — index members and catalog-only entries on identical terms, with the same per-component cache and reasoning prices and the long-context price ladder
data_get_scuCurrent Standard Compute Unit — value plus a methodology-versioned breakdown listing every family representative
data_get_breakdownPer-family blended-cost breakdown alone — methodology-versioned discriminated union with one entry per family representative
data_get_cpiFull Compute Price Index as last attested on-chain — scuUsd, revisionVersion, the raw and marked-up prices that revision published
data_get_reconstitutionsHistorical index changes — model swaps, SCU before/after
data_get_methodologyMethodology changelog — every version with its formula summary and spec link, plus the version in force
data_get_historySCU index time series over a date range — per-revision, daily, or weekly granularity; daily/weekly buckets carry the last revision's value forward across empty buckets
data_get_model_price_historyPer-model input/output USD price time series for any oracle-tracked model — same granularity semantics as data_get_history, with catchup gaps surfaced in unavailableRevisions
data_get_catalogEvery model with a recorded price, index members and non-index entries alike — indexMember flag, current price with its provenance pair, cache and reasoning components, and the raw upstream contextTiers / maxInputTokens
data_get_model_price_atPer-model input/output USD price effective at a timestamp — manifest source when the model represented its family in the revision active then, catalog otherwise
data_get_baselineFrozen SCU denominator behind computeIndex — the SCU of the first confirmed revision, set once and never recomputed
data_get_scu_atSCU value active at a timestamp via step function — no interpolation, null before the genesis revision
data_get_model_availabilityWhich models can serve right now — every catalogue model with a routable flag, the model auto points at, and the computedAt / ttlSeconds the answer is good for

Models are identified by their canonical vendor-prefixed id — anthropic/claude-opus-4.8, openai/gpt-5.5, qwen/qwen-3.5-flash. Every tool taking a model also accepts the bare name (gpt-5.5) and answers with the canonical id. The vendor slug is not always the provider key (alibaba → qwen, xai → x-ai, moonshot → moonshotai), so reuse an id the API returned rather than assembling one. data_get_scu, data_get_breakdown and data_get_reconstitutions are the exception: they pass the attested manifest through verbatim and so report bare model keys, because a / is not a legal manifest key.

Cache pricing comes from the Compute Finance Oracle. Session and consumption reports show effective (cache-aware) cost when the oracle has published the relevant cache components; otherwise they show nominal cost (input rate applied to every input variant) and label effective as unavailable for that model.

Alongside cache, the oracle publishes a reasoning output price — reasoning.reasoningOutput, on the same base as every other component; the whole reasoning block is null for a model with no usable reasoning price. It is catalogue data. Session and consumption reports do not bill it: Claude Code transcripts count thinking blocks rather than reasoning tokens, and those tokens are already inside output_tokens.

Every price is reported on two bases: base_* is the provider list price, identical for every model the oracle tracks, and billed_* is what compute.finance charges — base × (1 + routing_fee_rate). Compare models on base_*, budget on billed_*. The rate ships once per response and billed_* is null when the oracle does not publish it. Session and consumption reports are on the base basis throughout.

Every current-price answer comes from one place: the live catalogue the exchange bills against. Index membership decides which models data_get_basket and compute_compare list, never what a model costs, so two models the catalogue prices alike quote alike. data_get_cpi is the exception by design — it serves the prices the latest on-chain revision attested, which change only when an operator publishes the next one and may therefore lag the catalogue. Read it as attestation history, not as a quote.

Some models get pricier past a context length. data_get_basket and data_get_price publish that as context_tiers, a ladder ascending by from_input_tokens and always at least one rung: the first starts at 0 and restates the flat rate, so a model priced the same at every size has exactly one rung and nothing has to branch on whether a model happens to be tiered. Rungs carry base_* and billed_* like every other price; only the flat rate enters the SCU index. compute_estimate and compute_compare pick the rung from the whole input side of the request — prompt plus cache reads plus cache writes, all charged at the full input rate there since neither tool applies a cache discount — over half-open ranges, so an input landing exactly on a threshold takes that rung, and both return the chosen rung as applied_context_tier so the rate behind the number is visible. data_get_catalog passes the oracle document through unchanged, so there contextTiers is absent rather than one-rung on a flat model.

The ladder comes from the catalog endpoint, and the two kinds of tool part ways whenever it cannot answer for a model — the read failed, or it succeeded and the model was not in it, which is upstream drift rather than a flat price. data_get_basket and data_get_price still serve their prices and set context_tiers to null — an unknown ladder, never a one-rung stand-in for a ladder nobody read. compute_estimate and compute_compare error instead: a cost quoted at the flat rate would understate exactly the long context the ladder exists to price.

max_input_tokens is the largest input a model accepts, null when the model declares no window of its own — not unbounded: the request-body ceiling still applies, there is just no per-model limit. Above a declared window the oracle refuses the request outright, so compute_estimate and compute_compare set exceeds_max_input_tokens. They still quote the cost: these tools are read-only and an agent sizing a context needs the number before it reshapes the request, but the flag says plainly that the request as supplied would be rejected.

Prices also carry a provenance mark saying how far the number has been checked: verified — an operator recorded a vendor source for it; inferred — derived from a sibling number or a vendor default, with no source recorded; promotional — a discounted list price that is expected to end. Every value bills as shown; the mark says how much to trust it, not what it costs. Marks are set by hand and hold as of the operator's last pass, not as a live check against the vendor. Every cache and reasoning component carries its own mark wherever it appears, and so does every base price: data_get_catalog marks currentPrice.provenance for every model, index member or not, while data_get_basket, data_get_price and compute_estimate carry the same pair as base_price_provenance. A rung follows the same rule: the first repeats the base price's mark, and a higher rung is always a catalogue number, marked in both directions with the single mark the vendor quotes it under. Session and consumption reports print each cache multiplier with its mark; when the oracle publishes no cache pricing for a model they say so and print no marks.

A price says what a model costs, never whether it can serve. data_get_model_availability answers that second question: the public pool's routability list — every catalogue model under its canonical id with a routable flag, plus the model auto points at. Call it before settling on a model, so one that cannot serve is ruled out before the request instead of by a 503 after it. The signal is advisory: true as of computedAt and only for ttlSeconds after it, capacity moves on its own, and a model reported routable can still fail the send — the caller still handles the error on the request itself. The answer is the exchange's own, served verbatim with no liveness computed here, so it cannot disagree with the router that has to honour it; it is cached for exactly the ttlSeconds published with it, and not at all when that figure is missing or unusable, rather than for the window every other read use

只显示了开头部分;其余内容请在仓库中阅读

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