mcp
Live LLM API pricing: token prices, comparisons, cheapest-model lookups. No key required.
我該用這個嗎
品質與安全性
根據工具定義與協定合規性的自動化分析。
上下文成本
這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高，可用於其他工作的注意力就越少。
安裝
一鍵安裝
將以下內容加入你的 `claude_desktop_config.json` 檔案：
{
"mcpServers": {
"mcp": {
"command": "npx",
"args": [
"@modelpricewatch/mcp"
]
}
}
}可執行的套件
1.0.0stdio遠端端點
https://modelpricewatch.com/mcpstreamable-http它能做什麼
工具清單
工具（4）
🟢search_models(query, category, open_source, limit)
Search the live LLM pricing database by model name, provider, or id. Returns matching models with current input/output prices (USD per 1M tokens), context window, modality, and category. Use this to answer 'how much does <model> cost' or 'what models does <provider> offer'.
輸入結構描述
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Free-text match against model name, provider, or id (e.g. 'claude', 'gpt-5', 'gemini flash'). Omit to list all."
},
"category": {
"type": "string",
"description": "Filter by category, e.g. flagship, reasoning, budget, coding, embedding, fast, mid-tier."
},
"open_source": {
"type": "boolean",
"description": "If true, only open-source/open-weight models; if false, only proprietary."
},
"limit": {
"type": "number",
"description": "Max results (default 20, max 50)."
}
}
}🟢get_model_pricing(model_id)
Get full pricing and capability details for one model by its id (from search_models). Returns input/output/cached price per 1M tokens, blended cost, context window, modality, release date, and the modelpricewatch.com page URL.
輸入結構描述
{
"type": "object",
"properties": {
"model_id": {
"type": "string",
"description": "The model id, e.g. 'anthropic-claude-opus-4-8' or 'openai-gpt-5-5'. Get ids from search_models."
}
},
"required": [
"model_id"
]
}🟢cheapest_models(sort_by, category, open_source, limit)
Find the cheapest current models, ranked by input price, output price, or a blended cost. The generic ranking covers generative text models (embeddings, OCR and realtime models are excluded — they price different work); pass category to rank a specific pool instead, e.g. 'embedding'. Use to answer 'what is the cheapest model for <use case>'.
輸入結構描述
{
"type": "object",
"properties": {
"sort_by": {
"type": "string",
"description": "Ranking metric: 'input', 'output', or 'blended' (default 'blended')."
},
"category": {
"type": "string",
"description": "Filter by category, e.g. flagship, reasoning, budget, coding, embedding."
},
"open_source": {
"type": "boolean",
"description": "If true, only open-source models."
},
"limit": {
"type": "number",
"description": "How many to return (default 10, max 50)."
}
}
}🟢list_providers
List all tracked AI model providers (OpenAI, Anthropic, Google, etc.) with a short description and their pricing page.
輸入結構描述
{
"type": "object",
"properties": {}
}社群
證據