smolanalytics

your ai assistant admits it hallucinates your numbers. mine can't. it's a ci test.

The only analytics whose AI answer provably matches the dashboard. The agreement test runs in CI and fails the build if they ever differ. Ask "did activation improve this week?" right in Cursor or Claude Code and your own model answers from your real data over MCP, so there is no AI bill and no black box. It opens with a verdict that tells you what to fix. One MIT binary you run yourself, and your data never leaves your box.

_{That's the real product on demo data. Run it yourself in 30 seconds below. (still image)}

See it live, no install

smolanalytics-demo.fly.dev is the real product on demo data, running right now. The verdict up top, the ask bar, your events and pages as chips. Click checkout, or type "visitors to /pricing", and get the exact computed answer. The whole thing, one click away.

Run it yourself (30 seconds)

# Docker
docker run -p 8080:8080 ghcr.io/arjun0606/smolanalytics demo

or grab the binary:

curl -fsSL https://raw.githubusercontent.com/Arjun0606/smolanalytics/main/install.sh | sh
smolanalytics demo

or with Go:

go run github.com/Arjun0606/smolanalytics/cmd/smolanalytics@latest demo

Give it a few seconds to pull and seed, then open localhost:8080. Same fully populated dashboard, now on your machine. (If port 8080 is busy, use -p 8081:8080 and open localhost:8081.) The ask bar shows your real event names and pages as chips, so asking is a pick, not a guess: click checkout or type "visitors to /pricing" and get the exact computed answer.

Two ways to ask (and which is which)

smolanalytics answers plain-English questions on two surfaces. They are different, and keeping them straight is the whole model:

• The dashboard ask bar asks about your data. It's built in, zero setup, deterministic. It does not read your code: it knows your events and pages because they're in your data, and it shows them as chips so you never guess a name. Good for "how many checkout this week?", "visitors to /pricing", "where do people drop off?".
• Your coding agent over MCP (Cursor / Claude Code) asks code-aware questions. It has your codebase, your tracking plan (smolanalytics.plan.json), and smolanalytics over MCP, so it bridges the two: ask "what's the MAU for the PQR page" and the agent knows PQR is the /pqr route from your code, then queries smolanalytics for it. This is also where you instrument ("add tracking to the checkout flow I just built") and verify.

Recurring metrics never need re-typing: pin any report you build (or have your agent call save_report) and it renders on the dashboard every visit.

Why this exists

Every analytics tool now has an AI assistant, but it's bolted inside their app, you pay for it, and you still leave your editor to use it. smolanalytics flips it: the analytics comes to where you already work, answered by the model you already pay for.

• Ask in your editor, for free. It's an MCP server: connect Claude / Cursor / Claude Code a

... View full README on GitHub