lucius

lucius

Enables AI agents to render and interact with rich HTML one-pagers on a local canvas, with tools for rendering, commenting, selection, and status queries.

Category
Visit Server

README

lucius

The canvas your AI pair draws on.

Release License: MIT Platform Agent-native

You talk. Claude ships a page. Every pass is kept.

lucius is a desktop canvas where your coding agent renders rich, self-contained HTML one-pagers — architecture explorers, product briefs, interactive explainers, brainstorm artifacts — while you steer by voice or chat. Every push is an immutable version you can scrub. Highlight any sentence to comment. Publish to your own Cloudflare Worker, invite teammates by GitHub username, and watch their comments flow back into the app while the agent's live activity orb spins.

lucius — the welcome session rendering "how lucius works"

Set it up with Claude Code

Paste this into any Claude Code session — your agent does the rest:

Set up lucius (github.com/berkantay/lucius) on this machine:

1. macOS: run  curl -fsSL https://raw.githubusercontent.com/berkantay/lucius/main/install.sh | sh
   Linux: git clone https://github.com/berkantay/lucius, cd in, and follow SETUP.md instead.
2. Launch the app (open /Applications/lucius.app) and poll
   curl -s http://127.0.0.1:7317/api/ping until it answers {"app":"lucius","ok":true}.
3. Run ~/.lucius/src/scripts/doctor, execute every entry in missing_steps in
   order, and re-run doctor after each step. Never assume a step worked.
4. Run ~/.lucius/src/scripts/verify and do not report success until it prints
   VERIFY_OK and I confirm the app is showing "how lucius works".
5. Then follow the lucius-setup skill (~/.claude/skills/lucius-setup/SKILL.md)
   from Phase 2: ask me what I'm working on and render my first one-pager
   about it. Offer publishing and invites after.

Prefer doing it yourself? curl -fsSL https://raw.githubusercontent.com/berkantay/lucius/main/install.sh | sh, open the app, done. From-source and manual paths: SETUP.md.

Why lucius

  • Versions, not edits. Every iteration is an immutable snapshot in SQLite. The sidebar is a timeline per session; "wait, go back to the earlier one" is a click, not an apology.
  • Feedback lands on the exact thing you mean. Highlight text → comment, anchored to the phrase (tdoc-style anchors that survive new versions). Or point at any element with the crosshair — the agent reads exactly what you selected.
  • Sessions are workspaces. One per topic, each with its own history, comments, and a live thinking orb while an agent works it — visible to you in the sidebar and to your team on the published page.
  • Publish to infrastructure you own. One click puts a session on your Cloudflare Worker + R2 (free tier). Docs default to link-visibility; flip one private and invite GitHub usernames — uninvited visitors hit a sign-in gate. Viewer comments poll back into the app within a minute, and the agent replies on the page with what it changed.
  • Agent-native to the bone. A Claude Code skill encodes the artifact quality bar (truth rules: ground in real repos, never simplify the system; taste rules: strict monochrome, anti-slop list). An embedded MCP server (127.0.0.1:7317/mcp) exposes render/comment/selection/status tools to any session. Setup, repair, publishing, and invites are all driven by the lucius-setup onboarding skill — your agent operates the product, not you.
  • Taste is enforced, not hoped for. skill/design.md bans the AI-default looks by name (cream grounds, accent-color confetti, radius soup, stat-tile filler). Ink is the only accent.

The loop

 1 you talk        2 claude builds      3 new version      4 you review        5 publish
 voice · chat  ─▶  grounds, designs ─▶  immutable,    ─▶   scrub · point  ─▶   share · invite
 a screenshot      renders              instant            comment
        ▲                                                      │
        └────────────── "actually, make it layered" ───────────┘

The unit of feedback is a sentence, not a ticket. This repo was built in one day inside its own loop — the example artifact explaining it was written by Claude, rendered on the canvas it describes, and committed as the reference for what generated pages should look like.

Architecture

Claude Code ──(CLI / MCP, bearer token)──▶ control server (Rust, tiny_http :7317)
                                              │  SQLite: sessions · versions · comments
                                              │  Tauri events
                                              ▼
                                   app shell (React + Fluid Functionalism)
                                   layered sidebar · sandboxed iframe canvas
                                   highlight comments · selection · orbs
                                              │
                                   publish ──▶ your Cloudflare Worker + R2
                                              ◀── comment & status sync
Path What lives there
src-tauri/ Rust: SQLite store, control server + MCP, publish, comment poller
src/ React shell on Fluid Functionalism
skill/ The canvas skill: SKILL.md (workflow + truth rules), design.md (taste), lucius CLI
setup-skill/ The onboarding journey skill (install → first artifact → publish → invite)
worker/ Publish/comments worker, vendored from tdoc (MIT) with an access-control wrapper
scripts/ doctor (machine-readable state) · verify (proves the loop) · reset (replay first-run)
examples/ The reference artifact

Roadmap

  • A Claude per session — spawn a dedicated agent pinned to a workspace
  • In-app comment threads over the canvas (stored + anchored today; minimal UI)
  • Signed/notarized builds, Linux bundles
  • Own GitHub OAuth app for viewer sign-in (currently tdoc's shared client id)

Credits

Built by pairing with Claude, in one day, inside lucius itself. Standing on: tdoc (publish worker + comment overlay, MIT), Fluid Functionalism (shell components), thinking-orbs (activity orbs), Tauri and shadcn/ui.

License

MIT — see LICENSE.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured