目录 / //beforeyouship — LLM cost modeling from your editor
//beforeyouship — LLM cost modeling from your editor
Model the realistic monthly cost of an LLM app **before you build it**. Not a token calculator: retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth are modeled in, across GPT-5.x, Claude, Gemini, DeepSeek, and more. **Works without a key.** Connect and ask — demo mode covers the six free-tier models. A Pro API key ([beforeyouship.dev](https://beforeyouship.dev)) unlocks the full 18-model catalog. ## Tools | Tool | What it does | |---|---| - **`estimate_cost`** Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case $/mo per model, growth scenarios, and an opinionated recommendation. | - **`get_model_prices`** Current per-1M-token pricing (input, output, cached, batch) with context windows and staleness metadata. | - **`list_archetypes`** Seven preset architecture patterns (chatbot, RAG pipeline, multi-step agent, …) used as starting points for estimates. | ## Try it Paste into Claude Code or Cursor after connecting: > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day ## Setup ```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ``` ## Links - Docs & tool reference: https://beforeyouship.dev/docs#mcp - Live calculator: https://beforeyouship.dev - Announcement: https://beforeyouship.dev/blog/query-llm-costs-from-claude-code
接入信息
- 传输形态
- http
- 鉴权方式
- 鉴权未知
- 端点
https://cost-model--beforeyouship.run.tools
{
"mcpServers": {
"//beforeyouship — LLM cost modeling from your editor": {
"url": "https://cost-model--beforeyouship.run.tools"
}
}
}
能力清单
| 工具 | 说明 |
|---|---|
| list_archetypes | List the seven beforeyouship app archetypes (preset LLM architecture patterns) with their default usage parameters. Use an archetype id as the starting point for estimate_cost. |
| get_model_prices | Current per-1M-token pricing for all models in the beforeyouship catalog (input, output, cached input, batch), with context windows and pricing-staleness metadata. |
| estimate_cost | Model the realistic monthly cost of an LLM app architecture across models. Pick an archetype (see list_archetypes), give calls_per_day, and optionally override token counts and multipliers. Returns Naive / Realistic / Worst Case monthly costs, growth scenarios, and an opinionated model recommendation. |
提交举报 / 纠错
侵权举报经核验成立后,我们会即时下线该条目并删除已存的内容副本。