AiGanak LLM Cost

io.github.AiGanak由 GitHub 帳號 AiGanak 發布v2026.11.5更新於 Nov 7, 2026

LLM API prices, cost estimates, model comparisons and language token tax for GPT, Claude and Gemini.

已驗證STDIO僅桌面金融AI 與機器學習

概覽

AI 產生的概覽

本機 MCP 伺服器，讓助理查詢 OpenAI、Anthropic 與 Google 的 LLM API 現行價格、估算成本、比較模型，並查看各語言的 token 溢價。

可以做什麼
  • 列出模型及其每百萬 token 的標準、快取輸入與批次價格
  • 查詢單一模型的完整定價，含快取寫入、長上下文附加費與已公布的調價
  • 估算某模型上 N 次請求的成本，支援快取、批次與未來生效價格
  • 把同一負載在所有模型上比價，由最便宜排起
  • 測算同一段文字在 22 種語言中比英文多耗用多少 token，並估算指定文字的 token 數與成本
  • 查看附日期與來源的 LLM API 價格變動紀錄
適用情境
適合在規劃或編列 LLM 用量預算時使用：依成本比較模型、估算請求量開銷、了解調價影響，或在選定模型前評估多語言的 token 開銷。
執行需求
透過 npm 套件 @aiganak/llm-cost-mcp 以 stdio 在本機執行，需要 Node.js 18 或更新版本。不需 API 金鑰或帳號。啟動時會取得最新價格資料，離線時改用隨套件附帶的副本；設定 LLM_PRICES_OFFLINE=1 可一律使用附帶副本。
安裝前請注意
資料為 AiGanak 提供的第三方資料（CC BY 4.0），伺服器要求引用數字時註明 AiGanak 與核對日期。價格會變動，編列預算前應在各供應商官網確認。此伺服器為唯讀，只做估算，不呼叫供應商 API，也不會產生費用。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 AiGanak LLM Cost，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。

Desktop only，透過 STDIO。 STDIO 服務會啟動本機處理程序，因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

AiGanak LLM Cost MCP server

Ask your AI assistant what an LLM workload will cost, which model is cheapest for it, and how much more the same text costs in Hindi, German or Japanese, using current, sourced prices for OpenAI, Anthropic and Google models.

Works with any MCP client: Claude Desktop, Claude Code, Cursor, VS Code, Windsurf and others. No API key, no account.

Tools

ToolWhat it answers
list_modelsCurrent models with standard, cached-input and batch prices per million tokens
get_model_priceFull pricing for one model: cache writes, long-context surcharges, announced price changes, source page
estimate_costCost of N requests on one model, with caching, batch and future-dated prices
compare_modelsThe same workload priced on every model, cheapest first
token_taxHow many more tokens a language takes than English, per model family (22 languages)
estimate_text_costTokens and cost for a piece of text in any measured language, script detected automatically
price_changesDated, sourced log of LLM API price changes

Example questions:

  • "What will 50,000 requests of 6,000 input tokens (4,000 cached) and 500 output cost on Claude Sonnet 5.5 vs GPT-6.1 Sol?"
  • "Which model is cheapest for a Tamil support bot?"
  • "What does Gemini 4 Argon cost per request after its December price change?"

Install

Requires Node.js 18 or later.

Claude Desktop: add to claude_desktop_config.json:

json
{  "mcpServers": {    "aiganak-llm-cost": { "command": "npx", "args": ["-y", "@aiganak/llm-cost-mcp"] }  }}

Claude Code:

bash
claude mcp add aiganak-llm-cost -- npx -y @aiganak/llm-cost-mcp

Cursor: add the same mcpServers entry to ~/.cursor/mcp.json.

From source (no npm needed):

bash
git clone https://github.com/AiGanak/llm-prices && cd llm-prices/mcp && npm install# then use: "command": "node", "args": ["/path/to/llm-prices/mcp/index.js"]

Data

Prices, the price change log and the token tax index come from AiGanak/llm-prices (CC BY 4.0). The server fetches the latest data at start-up and falls back to the copy bundled with the package if it is offline (set LLM_PRICES_OFFLINE=1 to always use the bundled copy). Prices are checked weekly against each provider's own pricing page; the token tax is re-measured monthly with each provider's official token counter.

Prices change. Confirm on the provider's page before committing to a budget.

About

Built by AiGanak. We help teams cut LLM spend without losing quality: free tools at aiganak.com/tools, the LLM Cost Report and cost audits.

來源：mcp/README.md，提交 1b48694

工具

7

list_models

List LLM models and prices

List current OpenAI, Anthropic and Google API models with standard, cached-input and batch prices in USD per million tokens.

輸入參數tierprovider

get_model_price

Get one model's full pricing

Full pricing for one model: standard, cached input, cache write, batch, long-context surcharge, announced future price changes and the provider's source page.

輸入參數model必填

estimate_cost

Estimate the cost of LLM requests

Cost in USD of N requests on one model, with input/output breakdown, caching, batch, long-context surcharges and announced price changes.

輸入參數datebatchmodel必填requestsinput_tokens必填output_tokens必填cached_input_tokens

compare_models

Compare the same workload across models

Price the same request on every model (optionally one provider or tier), cheapest first. Use to choose a model on cost before testing quality.

輸入參數datetierbatchproviderrequestsinput_tokens必填output_tokens必填cached_input_tokens

token_tax

Language token tax

How many more tokens the same text takes in a language than in English, on each measured model (OpenAI GPT-6, Claude 5.x, Gemini 3.x, Gemini 4 Argon). 22 languages incl. Hindi, Tamil, German, Japanese. Omit language to list all.

輸入參數language

estimate_text_cost

Estimate tokens and cost for a text in any measured language

Estimate how many tokens a text takes on a model and what N such messages cost as input or output, using measured tokens-per-character for its language. Detects the script if language is omitted.

輸入參數astext必填model必填languagemessages

price_changes

Recent LLM API price changes

Dated, sourced log of LLM API price changes and pricing announcements (newest first).

輸入參數limit

版本歷史

1
  1. v2026.11.5最新Nov 6, 2026

評分

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