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Show HN: Modular – drop AI features into your app with two function calls
I kept hitting the same wall at work every time we needed to ship an AI feature. What looked like a week of work turned into picking a model, setting up a vector DB, managing embeddings, wiring up chat history, handling retries — none of it was the actual feature. So I built Modular. You register a function that returns your app's data, then call ai.run() for one-shot features or ai.chat() for stateful conversation. Everything else — context management, embeddings, session history, model routing, retries — is handled. MCP-native from day one. Works with Claude, GPT-4o, and Gemini. Still early — collecting feedback before building the full SDK. Would love to hear if others have hit this same wall, or if you think I'm solving the wrong problem.
Modular targets a high-growth market by simplifying the 'plumbing' of AI integration, leveraging the timely Model Context Protocol (MCP) to differentiate from legacy orchestration frameworks. However, the project is in its earliest stages with minimal traction and faces significant competition from established players like LangChain and Vercel AI SDK.