excalidraw-ai
Enables AI agents to read, watch, and edit live Excalidraw rooms by joining as a socket bot over a self-hosted relay, bypassing browser automation.
README
excalidraw-ai — MCP server (AI interface to Excalidraw)
The clean, non-clunky interface for an AI to read, watch, and edit a live Excalidraw room. Instead of browser automation (fiber-read + drag-drop + remote browser drops), it joins the room as a socket-bot over the collab relay and speaks the AES-GCM-encrypted scene protocol directly — deterministic, headless, scalable.
POC status: core bridge + MCP stdio surface working end-to-end against a
self-hosted excalidraw-room relay (selftest + MCP smoke pass).
Why a relay we control
The bot talks to a relay. Excalidraw's hosted relay
(oss-collab.excalidraw.com) origin-guards non-browser bots (403/400), so for
our own rooms we run excalidraw/excalidraw-room (MIT, same code as prod) and
point an Excalidraw UI at it via VITE_APP_WS_SERVER_URL.
Architecture
Excalidraw UI (fork) ──socket.io──▶ relay (excalidraw-room) ◀──socket-bot── excalidraw-ai (MCP)
(humans) self-hosted (the AI's interface)
Tools
| Tool | What it does |
|---|---|
create_room |
new room id/key for our relay |
join_room |
join a room, read scene, start listening |
leave_room |
disconnect |
get_scene |
board elements + texts |
get_changes |
add/update/remove deltas since last call ("hear the room") |
add_elements |
append elements (broadcast live) |
update_elements |
move / retitle / recolor existing (version bump) |
delete_elements |
mark deleted |
Run
npm install
# relay (one terminal):
cd /tmp/excalidraw-room && PORT=3002 node dist/index.js
# self-test the bridge core:
npm run selftest
# MCP smoke (stdio handshake + join + get_scene):
npm run mcp-smoke
# start the MCP server (stdio) — wire into Hermes/Copilot/Claude:
node src/server.js
Wire into Hermes (~/.hermes/config.yaml)
The server can run two ways:
Local (stdio) — spawn as a subprocess:
mcp_servers:
excalidraw_ai:
command: node
args: ["/root/workspace/mcclawd-org/excalidraw-ai/src/server.js"]
Deployed on a VPS (HTTP / StreamableHTTP) — reach it over the network with token auth. See the Deploy section below.
mcp_servers:
excalidraw_ai:
url: "http://<vps>:4000/mcp"
headers:
Authorization: "Bearer <EXCALIDRAW_AI_TOKEN>"
timeout: 90
Restart Hermes → tools appear as mcp_excalidraw_ai_*.
Deploy (VPS, PM2)
Run the server as a headless service next to the relay. Currently deployed to
72.62.115.153 (srv1544821): relay :3002, MCP :4000 (token-authed), under
PM2 (excalidraw-room, excalidraw-ai), ecosystem.config.cjs in this repo.
# on the VPS
# /opt/excalidraw-room (relay: PORT=3002 node dist/index.js)
# /opt/excalidraw-ai (MCP: node src/server-http.js)
cd /opt/excalidraw-ai && npm ci
# put EXCALIDRAW_AI_TOKEN=<long-random> into /opt/excalidraw-ai/.env (chmod 600)
pm2 start ecosystem.config.cjs && pm2 save && pm2 startup systemd
# firewall: ufw allow 3002/tcp 4000/tcp
Endpoints: GET /health, POST/GET /mcp (StreamableHTTP). Unauthorized
requests → 401. Hardening note: TLS via nginx+Let's Encrypt still TODO.
Layout
src/crypto.js— AES-GCM E2E helpers (Node Web Crypto)src/elements.js— element builders + scene merge/diff (id+version semantics)src/room.js— RoomClient: socket join, read, write, change feedsrc/app.js— shared tool registration (used by both entrypoints)src/server.js— MCP stdio entrypointsrc/server-http.js— MCP HTTP entrypoint (token auth + /health)ecosystem.config.cjs— PM2 config for relay + server (ESM-safe)scripts/selftest.mjs,scripts/mcp-smoke.mjs— verification
Recommended Servers
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.