//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
https://cost-model--beforeyouship.run.tools
How to connect
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Smithery (hosted)
1. Open https://smithery.ai/servers/beforeyouship/cost-model 2. Click Connect and complete OAuth in your MCP client (Claude, Cursor, VS Code, etc.) 3. MCP endpoint: https://cost-model--beforeyouship.run.tools
Tools (3)
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list_archetypesList 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.
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get_model_pricesCurrent per-1M-token pricing for all models in the beforeyouship catalog (input, output, cached input, batch), with context windows and pricing-staleness metadata.
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estimate_costModel 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.