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okf-kit

CI PyPI Python versions License: Apache 2.0 OKF spec

Turn any website into a portable, agent-ready knowledge bundle — no LLM required to start.

okf-kit crawls a site into a Google Open Knowledge Format (OKF) bundle: a directory of markdown concept files with YAML frontmatter and per-directory index.md listings that any agent can navigate with plain file reads. Build it, keep it in sync as the site changes, publish it, and chat with it — locally, with your own key, or fully offline via Ollama.

pip install okf-kit
okf build https://docs.example.com -o docs-okf   # crawl → OKF bundle (no key, no browser)
okf chat docs-okf --provider ollama              # chat offline, no key

Or zero-install with uv:

uvx --from okf-kit okf build https://docs.example.com -o docs-okf

Part of the calknowledge ecosystem — okf-kit is the lightweight, open library; calknowledge is the full platform (LLM enrichment, RAG export, retrieval evals, GUI) built on top of it.


Why

Everyone re-crawls and re-indexes the same docs privately and badly. okf-kit makes a website's knowledge a portable artifact:

  • Agents can read an OKF bundle; they can't read your website. The bundle is navigable markdown — no scraping, no SDK, no runtime.

  • Faithful markdown, not text soup. Real extraction (headings, code, tables), boilerplate filtered, JS-rendered when needed.

  • Self-maintaining. okf sync updates only what changed, so a published bundle in git produces small delta commits and never goes stale.

  • Works with any LLM, or none. Chat via OpenAI, Ollama, vLLM, OpenRouter, or Claude — or get a zero-key retrieval answer with citations.

Related MCP server: Web Scraper MCP Server

Install

pip install okf-kit                 # core: build / sync / validate / zip / list / get / visualize
pip install "okf-kit[chat]"         # okf chat via OpenAI-compatible providers (OpenAI, Ollama, …)
pip install "okf-kit[anthropic]"    # Claude as a chat provider
pip install "okf-kit[js]"           # crawl JavaScript-rendered sites (pulls a Playwright Chromium)
pip install "okf-kit[mcp]"          # serve bundles to Claude Code / Cursor over MCP
pip install "okf-kit[enrich]"       # okf build --enrich (LLM descriptions + tags)

The default install has no browser and no LLM SDK — it installs in seconds.

Tip: install into a dedicated virtualenv so okf-kit's dependencies don't mix with your other projects:

python3 -m venv ~/okf && ~/okf/bin/pip install okf-kit

This also avoids clashes if an existing environment already pins packages like lxml (e.g. a prior crawl4ai install) — a plain install would otherwise bump them.

Commands

Build

okf build https://docs.example.com -o docs-okf --max-depth 3 --max-pages 200

Domain-restricted BFS crawl → an OKF bundle: pages/ mirror with frontmatter concepts, a .okf-kit/state.json for sync, and an index.md in every directory for agent navigation. Validated on exit. No API key needed.

By default the crawl is scoped to the seed's path sectionokf build https://doc.rust-lang.org/book/ stays under /book/ and won't wander into the rest of the host. Override with --path-prefix PATH (a narrower/different scope) or --all-paths (the whole host). Other flags: --js (JS-rendered sites — build hints when a site needs it), --no-robots, --enrich (add LLM descriptions/tags — needs [enrich] + OPENAI_API_KEY).

Sync

okf sync docs-okf

Re-crawls the same site and updates only the delta — added pages written, changed pages rewritten, removed pages deleted, unchanged pages left byte-for-byte (stable git diffs). A safety valve aborts on a suspiciously empty re-crawl (--force overrides).

Chat

okf chat docs-okf --provider ollama                 # offline, no key
okf chat docs-okf --provider openai --trace         # any provider, with citations + a navigation trace
okf chat docs-okf                                   # no provider → zero-key retrieval answer
okf chat docs-okf --resume                          # continue the last session (history is local)

The agent navigates the bundle (list_directory / read_concept) to the most specific concept and answers only from what it read, citing the paths.

--provider

Endpoint

Key

openai

OpenAI

OPENAI_API_KEY

ollama

localhost:11434 (local)

none

openrouter

OpenRouter

OPENROUTER_API_KEY

anthropic

Claude

ANTHROPIC_API_KEY

custom

--base-url

as configured

Chat history is stored locally at ~/.okf/chats/<bundle>/.

Visualize

okf visualize docs-okf          # -> docs-okf/graph.html

A self-contained interactive graph (nodes = concepts, edges = internal links); no backend, no CDN — open the HTML from file://.

Serve over MCP

okf serve-mcp docs-okf          # or --all for every downloaded bundle

Exposes list_bundles / list_directory / read_concept / search_bundle over stdio MCP for Claude Code/Desktop, Cursor, and any MCP client.

Or run it as a container (the included Dockerfile bakes in the rust-book bundle):

docker build -t okf-kit-mcp .
docker run -i --rm okf-kit-mcp   # speaks MCP over stdio; serve another bundle: … okf-kit-mcp okf serve-mcp <name>

Registry

okf list --remote               # browse published bundles
okf get backstage-docs          # download, validate, install to ~/.okf/bundles/
okf list                        # your local bundles

Package for hand-off

okf zip docs-okf                # -> docs-okf.zip, ready to publish or share

Publishing

See docs/PUBLISHING.md — build a bundle, ship it as a release zip with a weekly self-sync Action, and add it to the awesome-okf-kit registry. Publish only content you may redistribute.

Bundle layout

docs-okf/
    index.md                 root directory listing (reserved, no frontmatter)
    log.md                   build/sync history
    pages/                   one concept per page (frontmatter + body + citations)
        index.md             directory listing (every directory has one)
        home.md
        docs/…
    .okf-kit/state.json      crawl config, per-page content hashes, link edges

Development

pip install -e ".[dev]", then pytest -q (37 tests, fully offline) and ruff check okf_kit tests. See CONTRIBUTING.md and the CHANGELOG.

License

Apache-2.0.

A
license - permissive license
-
quality - not tested
A
maintenance

Maintenance

Maintainers
<1hResponse time
0dRelease cycle
10Releases (12mo)
Commit activity

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