I built a framework on top of FastAPI because I got tired of making the same 12 decisions every project
Every FastAPI project I started felt identical. Pick an async ORM, wire migrations, build an admin panel, standardize serialization, write the glue. Same decisions, different project.
Yes, boilerplates exist. But a boilerplate is something you fork and maintain forever, the assembly decisions just move into your codebase. Every new model, you're back to writing the same wiring.
So I built Aksara. It sits on top of FastAPI, you keep the full ecosystem and performance and handles the repetitive assembly. Define a model once and get:
- Full REST API
- Admin dashboard
- Studio UI at /studio/ui to inspect your backend visually
- AI Console — ask your live backend questions in plain English
- MCP tool catalog at /ai/tools/mcp — Claude, Cursor, any MCP client can call your API directly
The piece I'm proudest of is field-level AI metadata. ai_sensitive=True removes a field from AI context and the MCP schema entirely. ai_agent_writable=False lets agents read but not modify. Write it once on the model, propagates everywhere.
Five commands from zero to running:
bash
pip install aksara-framework
aksara startproject myapp && cd myapp
aksara dbsetup
aksara migrate
aksara dev
It's pre-1.0, backed by 6378 tests, and honest about its rough edges.
GitHub: https://github.com/nagarjuna-tella/Aksara Docs: https://nagarjuna-tella.github.io/Aksara/
Happy to answer questions or take criticism, built this nights and weekends and genuinely want to know what's wrong with it.