MCP服务器 + 本地模型：领域特定AI工具的零API成本
MCP服务器与微调本地模型的结合消除了基于Claude、Cursor和其他MCP兼容客户端构建的AI工具的按token成本。
标准AI工具架构：你的应用调用Claude或GPT-4 API，按token付费。替代架构：你的应用暴露由本地微调模型支持的MCP工具。AI客户端调用工具，工具调用你的本地模型。领域推理零API成本。
成本结构对比
标准架构每次调用$0.005-0.03。MCP + 本地模型架构每次调用约$0.001计算成本。
构建零成本工具的模式
- 在Ertas中训练领域模型，导出为GGUF，部署到Ollama
- 构建暴露领域能力的MCP服务器
- 发布MCP服务器供用户安装
- 通过模型盈利，而非调用次数 — 收取平访月订阅
商业模式转变
之前：构建工具，每次使用你付费。之后：工具调用命中你的Ollama服务器。基础设施成本$40-80/月固定。利润率随使用量改善而非压缩。
Ship AI that runs on your users' devices.
Ertas early bird pricing starts at $14.50/mo — locked in for life. Plans for builders and agencies.
延伸阅读
Ship AI that runs on your users' devices.
Early bird pricing starts at $14.50/mo — locked in for life. Plans for builders and agencies.
Keep reading
Shopify AI Assistant Without OpenAI API Costs: The Local Model Approach
Shopify stores spending $500-5,000/month on AI API costs can replace those calls with a local fine-tuned model. Here's the architecture, the Shopify integration, and the cost math.
EdTech AI Cost Reduction: Replace OpenAI API Calls With a Fine-Tuned Subject Model
EdTech platforms spending $2,000-15,000/month on OpenAI API for tutoring, feedback, and assessment can replace most of that spend with a fine-tuned local model at $20-40/month in infrastructure.
MCP + Fine-Tuned Local Model: Connect Claude to Your Domain-Specific AI
Model Context Protocol (MCP) lets Claude Desktop talk to any server — including your own Ollama-hosted fine-tuned model. Here's the architecture and setup for routing Claude requests to a custom domain model.