FREE · OPEN SOURCE · MIT

Ship your AI the docs —
and the graph.

One command downloads a library's docs as Markdown plus a pre-built knowledge graph, pinned to a release. Far better context for your AI, at a fraction of the tokens.

$uvx graflet react
react — graflet · example output
$ uvx graflet react
 Resolved react@19.1.0 (pinned)
 Downloaded docs → ./graflet/react/*.md (312 files)
 Fetched knowledge graph → graph.json (1,204 nodes · 3,880 edges)
 Aligned to release react@19.1.0
Done in 8m 12s · saved ~$0.42 in build cost

Knowledge-graph catalog

aligned to pinned releases
LibraryVersionGraphScoreTokens savedGraph sizeUpdatedCommand
Loading catalog…
01 · MARKDOWN

Docs as Markdown

Every page of the official docs, downloaded as clean Markdown you can grep, feed, and version — pinned to the exact release you install.

02 · THE VALUE

Knowledge graph

A pre-built graph of concepts, APIs, and how they connect — as an interactive view and a machine-readable graph.json. This is the context your AI actually needs.

Build cost saved
vs building the graph yourself
Build time done
pre-computed, not on your machine
GraphScore
coverage × structure quality
Fewer tokens for your AI
vs feeding raw docs

Live from the catalog · — until the first graph is measured

How it works

01

Run one command

uvx graflet react — no config, no account to start.

02

Sign in with GitHub

One click, and only to download the graph. Install, browse and copy stay free.

03

We fetch both

Docs pulled from the upstream project, the knowledge graph from our backend.

04

Land locally, aligned

docs/*.md and graph.json on disk, pinned to the same release.

WHY A KNOWLEDGE GRAPH

Raw docs are flat. A graph knows how things connect.

The graph encodes relationships — which API calls which, what depends on what, which concepts connect — so your AI retrieves the right context instead of dumping whole pages. Cheaper prompts, sharper answers, fewer hallucinations.

Support the project

Free and open source. No paid plans — ever.