dotplot-mcp

Dot Plot MCP

See individual users, not aggregate charts.

English | 한국어

Install

Paste this to your agent and it sets everything up:

Set up Dotplot (MCP + skills) — instructions are here https://dotplot-reports.vercel.app/setup.md

Or do it by hand

claude mcp add --scope user dotplot -- uvx dotplot-mcp

Use

Say this in any project:

"Analyze my product"

You get the report above. That's it.

Or use the slash commands:

/dotplot-analyze-product    full analysis and report
/dotplot-add-tracking       find and write the logging you're missing
/dotplot-whats-changed      compare with the previous report

Claude finds your data, picks the action that means "this user got value", and writes the report. No events table needed — your orders table already is one:

SELECT user_id, created_at::date AS date, 'purchase' AS event FROM orders
UNION ALL
SELECT user_id, added_at::date, 'add_to_wishlist' FROM wishlist_items

Nothing tracked yet? Say "add the tracking I'm missing" and Claude reads your code, writes the logging that's absent, and tells you when to come back.

No product to analyze yet? Try the sample

git clone https://github.com/brownglasses/dotplot-mcp && cd dotplot-mcp
uv run sample_data.py   # 40 fake users with a pattern planted in them
uv run harness.py       # watch the whole pipeline run

Why this exists

DAU/MAU charts go "up and to the right" as long as new users arrive — even when nobody stays. Until you have hundreds of users, the most informative dashboard is YC's dot plot (David Lieb): one row per user, one cell per day.

Four rules keep it honest:

• Code computes, AI only interprets — same data, same numbers, every time
• Small samples withhold judgment — under 5 users in a group, it says nothing
• Correlation isn't cause — every finding ships with "test this before you believe it"
• Vanity metrics are refused — pick open_app as your value event and the code says no

Reports come out in your language (English, 한국어, 日本語 built in; anything else translated on the fly with the numbers verified intact).

More

• What each tool does, and the anonymous benchmark
• How it's built

MIT