TL;DR verdict: Use Streamlit Community Cloud for your one free public demo or your single private app. Use AgentCell when the team has five or ten Python tools — FastAPI reconcilers, Streamlit explorers, ops dashboards — each shared with a different three colleagues.
Where Streamlit wins (honestly)
- Zero-config Python. Push a script, get a data app. Nothing in our plan changes the fact that Streamlit invented this workflow.
- Free. Genuinely free for public apps — Snowflake-owned, not monetized, no credit arithmetic.
- Community. The gallery, the forum, the “how do I…” answers for every widget.
The one-private-app cliff
The free tier’s terms are precise: exactly one private app, ever. 1GB RAM. 12-hour idle sleep. That is not a funnel — it is a ceiling. Your second private tool, your fifth, your tenth: there is nowhere for them to go on this platform. Teams respond by making internal tools public (don’t), by sharing one login (don’t), or by leaving tools on laptops (the status quo we’re all trying to kill).
This cap is also a revealed preference: Streamlit, PythonAnywhere, Heroku, and Fly have all shrunk or killed free tiers for permanently-tiny apps. The industry is moving away from serving the permanently small — which is why our model starts from “unlimited cells, free idle” rather than bolting it on.
How AgentCell handles Python cells (stated plainly)
A large share of agent-built small software is Python — Streamlit, FastAPI — and the cheapest serving tiers (Workers, Deno) are JS/WASM-only. Resolving near-zero-idle Python is a design problem we measure before launch, not a footnote: per-cell sleep cost and wake latency for Python cells specifically, published before any pricing. What we commit to is the shape: runtime auto-detection from the folder, a per-cell datastore so tracking tools work, a share list instead of “one private slot,” and colleagues signing in with work accounts instead of a shared password.
Side-by-side
| Streamlit Community Cloud | AgentCell | |
|---|---|---|
| Private apps | Exactly one, ever | Unlimited cells |
| RAM / sleep | 1GB, 12-hour sleep | Sized per cell; sleep-to-zero design |
| Frameworks | Streamlit (Python) | Streamlit, FastAPI/Flask, Node, static |
| Share with 3 colleagues | Not beyond the one slot | Per-cell share list, no auth code |
| Data | External only | Per-cell datastore + object storage |
| Best for | One public demo, one private tool | A team’s whole shelf of Python tools |
Fit checklist
Use AgentCell when: private tool #2 exists or is imaginable; different tools have different audiences; the team wants work-login sharing, not link-with-password.
Stay on Streamlit Cloud when: one public demo or a single private app covers the need; free-forever for that shape beats every alternative.
FAQ
Can I deploy my existing streamlit app.py unchanged?
That is the design goal: folder in, runtime detected, URL out. Streamlit is explicitly in the v1 detection list. Today it needs a Dockerfile; the samples repository has a Streamlit app with one.
What about heavy compute (large dataframes, ML inference)? Small-tools state and interaction, yes. Sustained heavy compute belongs on specialized infra — the always-on fallback tier exists for runtimes that need it, priced accordingly.
Got more private Streamlit apps than Streamlit allows? Deploy now.