# Excalidraw MCP Server & Agent Skill

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Run a live Excalidraw canvas and control it from AI agents. This repo provides:

- **MCP Server**: Connect via Model Context Protocol (Claude Desktop, Cursor, Codex CLI, etc.)
- **Agent Skill**: Portable skill for Claude Code, Codex CLI, and other skill-enabled agents

Keywords: Excalidraw agent skill, Excalidraw MCP server, AI diagramming, Claude Code skill, Codex CLI skill, Claude Desktop MCP, Cursor MCP, Mermaid to Excalidraw.

## Demo

![MCP Excalidraw Demo](demo.gif)

*AI agent creates a complete architecture diagram from a single prompt (4x speed). [Watch full video on YouTube](https://youtu.be/ufW78Amq5qA)*

## Table of Contents

- [Demo](#demo)
- [What It Is](#what-it-is)
- [How We Differ from the Official Excalidraw MCP](#how-we-differ-from-the-official-excalidraw-mcp)
- [What's New](#whats-new)
- [Quick Start (Local)](#quick-start-local)
- [Quick Start (Docker)](#quick-start-docker)
- [Configure MCP Clients](#configure-mcp-clients)
  - [Claude Desktop](#claude-desktop)
  - [Claude Code](#claude-code)
  - [Cursor](#cursor)
  - [Codex CLI](#codex-cli)
  - [OpenCode](#opencode)
  - [Antigravity (Google)](#antigravity-google)
- [Agent Skill (Optional)](#agent-skill-optional)
- [MCP Tools (26 Total)](#mcp-tools-26-total)
- [Testing](#testing)
- [Troubleshooting](#troubleshooting)
- [Known Issues / TODO](#known-issues--todo)
- [Development](#development)

## What It Is

This repo contains two separate processes:

- Canvas server: web UI + REST API + WebSocket updates (default `http://localhost:3000`)
- MCP server: exposes MCP tools over stdio; syncs to the canvas via `EXPRESS_SERVER_URL`

## How We Differ from the Official Excalidraw MCP

Excalidraw now has an [official MCP](https://github.com/excalidraw/excalidraw-mcp) — it's great for quick, prompt-to-diagram generation rendered inline in chat. We solve a different problem.

| | Official Excalidraw MCP | This Project |
|---|---|---|
| **Approach** | Prompt in, diagram out (one-shot) | Programmatic element-level control (26 tools) |
| **State** | Stateless — each call is independent | Persistent live canvas with real-time sync |
| **Element CRUD** | No | Full create / read / update / delete per element |
| **AI sees the canvas** | No | `describe_scene` (structured text) + `get_canvas_screenshot` (image) |
| **Iterative refinement** | No — regenerate the whole diagram | Draw → look → adjust → look again, element by element |
| **Layout tools** | No | `align_elements`, `distribute_elements`, `group / ungroup` |
| **File I/O** | No | `export_scene` / `import_scene` (.excalidraw JSON) |
| **Snapshot & rollback** | No | `snapshot_scene` / `restore_snapshot` |
| **Mermaid conversion** | No | `create_from_mermaid` |
| **Shareable URLs** | Yes | Yes — `export_to_excalidraw_url` |
| **Design guide** | `read_me` cheat sheet | `read_diagram_guide` (colors, sizing, layout, anti-patterns) |
| **Viewport control** | Camera animations | `set_viewport` (zoom-to-fit, center on element, manual zoom) |
| **Live canvas UI** | Rendered inline in chat | Standalone Excalidraw app synced via WebSocket |
| **Multi-agent** | Single user | Multiple agents can draw on the same canvas concurrently |
| **Works without MCP** | No | Yes — REST API fallback via agent skill |

**TL;DR** — The official MCP generates diagrams. We give AI agents a full canvas toolkit to build, inspect, and iteratively refine diagrams — including the ability to see what they drew.

## What's New

### v2.0 — Canvas Toolkit

- 13 new MCP tools (26 total): `get_element`, `clear_canvas`, `export_scene`, `import_scene`, `export_to_image`, `duplicate_elements`, `snapshot_scene`, `restore_snapshot`, `describe_scene`, `get_canvas_screenshot`, `read_diagram_guide`, `export_to_excalidraw_url`, `set_viewport`
- **Closed feedback loop**: AI can now inspect the canvas (`describe_scene`) and see it (`get_canvas_screenshot` returns an image) — enabling iterative refinement
- **Design guide**: `read_diagram_guide` returns best-practice color palettes, sizing rules, layout patterns, and anti-patterns — dramatically improves AI-generated diagram quality
- **Shareable URLs**: `export_to_excalidraw_url` encrypts and uploads the scene to excalidraw.com, returns a shareable link anyone can open
- **Viewport control**: `set_viewport` with `scrollToContent`, `scrollToElementId`, or manual zoom/offset — agents can auto-fit diagrams after creation
- **File I/O**: export/import full `.excalidraw` JSON files
- **Snapshots**: save and restore named canvas states
- **Skill fallback**: Agent skill auto-detects MCP vs REST API mode, gracefully falls back to HTTP endpoints when MCP server isn't configured
- Fixed all previously known issues: `align_elements` / `distribute_elements` fully implemented, points type normalization, removed invalid `label` type, removed HTTP transport dead code, `ungroup_elements` now errors on failure

### v1.x

- Agent skill: `skills/excalidraw-skill/` (portable instructions + helper scripts for export/import and repeatable CRUD)
- Better testing loop: MCP Inspector CLI examples + browser screenshot checks (`agent-browser`)
- Bugfixes: batch create now preserves element ids (fixes update/delete after batch); frontend entrypoint fixed (`main.tsx`)

## Quick Start (Local)

Prereqs: Node >= 18, npm

```bash
npm ci
npm run build
```

Terminal 1: start the canvas
```bash
HOST=0.0.0.0 PORT=3000 npm run canvas
```

Open `http://localhost:3000`.

Terminal 2: run the MCP server (stdio)
```bash
EXPRESS_SERVER_URL=http://localhost:3000 node dist/index.js
```

## Quick Start (Docker)

Canvas server:
```bash
docker run -d -p 3000:3000 --name mcp-excalidraw-canvas ghcr.io/yctimlin/mcp_excalidraw-canvas:latest
```

MCP server (stdio) is typically launched by your MCP client (Claude Desktop/Cursor/etc.). If you want a local container for it, use the image `ghcr.io/yctimlin/mcp_excalidraw:latest` and set `EXPRESS_SERVER_URL` to point at the canvas.

## Configure MCP Clients

The MCP server runs over stdio and can be configured with any MCP-compatible client. Below are configurations for both **local** (requires cloning and building) and **Docker** (pull-and-run) setups.

### Environment Variables

| Variable | Description | Default |
|----------|-------------|---------|
| `EXPRESS_SERVER_URL` | URL of the canvas server | `http://localhost:3000` |
| `ENABLE_CANVAS_SYNC` | Enable real-time canvas sync | `true` |

---

### Claude Desktop

Config location:
- macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
- Windows: `%APPDATA%\Claude\claude_desktop_config.json`
- Linux: `~/.config/Claude/claude_desktop_config.json`

**Local (node)**
```json
{
  "mcpServers": {
    "excalidraw": {
      "command": "node",
      "args": ["/absolute/path/to/mcp_excalidraw/dist/index.js"],
      "env": {
        "EXPRESS_SERVER_URL": "http://localhost:3000",
        "ENABLE_CANVAS_SYNC": "true"
      }
    }
  }
}
```

**Docker**
```json
{
  "mcpServers": {
    "excalidraw": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "EXPRESS_SERVER_URL=http://host.docker.internal:3000",
        "-e", "ENABLE_CANVAS_SYNC=true",
        "ghcr.io/yctimlin/mcp_excalidraw:latest"
      ]
    }
  }
}
```

---

### Claude Code

Use the `claude mcp add` command to register the MCP server.

**Local (node)** - User-level (available across all projects):
```bash
claude mcp add excalidraw --scope user \
  -e EXPRESS_SERVER_URL=http://localhost:3000 \
  -e ENABLE_CANVAS_SYNC=true \
  -- node /absolute/path/to/mcp_excalidraw/dist/index.js
```

**Local (node)** - Project-level (shared via `.mcp.json`):
```bash
claude mcp add excalidraw --scope project \
  -e EXPRESS_SERVER_URL=http://localhost:3000 \
  -e ENABLE_CANVAS_SYNC=true \
  -- node /absolute/path/to/mcp_excalidraw/dist/index.js
```

**Docker**
```bash
claude mcp add excalidraw --scope user \
  -- docker run -i --rm \
  -e EXPRESS_SERVER_URL=http://host.docker.internal:3000 \
  -e ENABLE_CANVAS_SYNC=true \
  ghcr.io/yctimlin/mcp_excalidraw:latest
```

**Manage servers:**
```bash
claude mcp list              # List configured servers
claude mcp remove excalidraw # Remove a server
```

---

### Cursor

Config location: `.cursor/mcp.json` in your project root (or `~/.cursor/mcp.json` for global config)

**Local (node)**
```json
{
  "mcpServers": {
    "excalidraw": {
      "command": "node",
      "args": ["/absolute/path/to/mcp_excalidraw/dist/index.js"],
      "env": {
        "EXPRESS_SERVER_URL": "http://localhost:3000",
        "ENABLE_CANVAS_SYNC": "true"
      }
    }
  }
}
```

**Docker**
```json
{
  "mcpServers": {
    "excalidraw": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "EXPRESS_SERVER_URL=http://host.docker.internal:3000",
        "-e", "ENABLE_CANVAS_SYNC=true",
        "ghcr.io/yctimlin/mcp_excalidraw:latest"
      ]
    }
  }
}
```

---

### Codex CLI

Use the `codex mcp add` command to register the MCP server.

**Local (node)**
```bash
codex mcp add excalidraw \
  --env EXPRESS_SERVER_URL=http://localhost:3000 \
  --env ENABLE_CANVAS_SYNC=true \
  -- node /absolute/path/to/mcp_excalidraw/dist/index.js
```

**Docker**
```bash
codex mcp add excalidraw \
  -- docker run -i --rm \
  -e EXPRESS_SERVER_URL=http://host.docker.internal:3000 \
  -e ENABLE_CANVAS_SYNC=true \
  ghcr.io/yctimlin/mcp_excalidraw:latest
```

**Manage servers:**
```bash
codex mcp list              # List configured servers
codex mcp remove excalidraw # Remove a server
```

---

### OpenCode

Config location: `~/.config/opencode/opencode.json` or project-level `opencode.json`

**Local (node)**
```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "excalidraw": {
      "type": "local",
      "command": ["node", "/absolute/path/to/mcp_excalidraw/dist/index.js"],
      "enabled": true,
      "environment": {
        "EXPRESS_SERVER_URL": "http://localhost:3000",
        "ENABLE_CANVAS_SYNC": "true"
      }
    }
  }
}
```

**Docker**
```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "excalidraw": {
      "type": "local",
      "command": ["docker", "run", "-i", "--rm", "-e", "EXPRESS_SERVER_URL=http://host.docker.internal:3000", "-e", "ENABLE_CANVAS_SYNC=true", "ghcr.io/yctimlin/mcp_excalidraw:latest"],
      "enabled": true
    }
  }
}
```

---

### Antigravity (Google)

Config location: `~/.gemini/antigravity/mcp_config.json`

**Local (node)**
```json
{
  "mcpServers": {
    "excalidraw": {
      "command": "node",
      "args": ["/absolute/path/to/mcp_excalidraw/dist/index.js"],
      "env": {
        "EXPRESS_SERVER_URL": "http://localhost:3000",
        "ENABLE_CANVAS_SYNC": "true"
      }
    }
  }
}
```

**Docker**
```json
{
  "mcpServers": {
    "excalidraw": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "EXPRESS_SERVER_URL=http://host.docker.internal:3000",
        "-e", "ENABLE_CANVAS_SYNC=true",
        "ghcr.io/yctimlin/mcp_excalidraw:latest"
      ]
    }
  }
}
```

---

### Notes

- **Docker networking**: Use `host.docker.internal` to reach the canvas server running on your host machine. On Linux, you may need `--add-host=host.docker.internal:host-gateway` or use `172.17.0.1`.
- **Canvas server**: Must be running before the MCP server connects. Start it with `npm run canvas` (local) or `docker run -d -p 3000:3000 ghcr.io/yctimlin/mcp_excalidraw-canvas:latest` (Docker).
- **Absolute paths**: When using local node setup, replace `/absolute/path/to/mcp_excalidraw` with the actual path where you cloned and built the repo.
- **In-memory storage**: The canvas server stores elements in memory. Restarting the server will clear all elements. Use the export/import scripts if you need persistence.

## Agent Skill (Optional)

This repo includes a skill at `skills/excalidraw-skill/` that provides:

- **Workflow playbook** (`SKILL.md`): step-by-step guidance for drawing, refining, and exporting diagrams
- **Cheatsheet** (`references/cheatsheet.md`): MCP tool and REST API reference
- **Helper scripts** (`scripts/*.cjs`): export, import, clear, healthcheck, CRUD operations

The skill complements the MCP server by giving your AI agent structured workflows to follow.

### Install The Skill (Codex CLI example)

```bash
mkdir -p ~/.codex/skills
cp -R skills/excalidraw-skill ~/.codex/skills/excalidraw-skill
```

To update an existing installation, remove the old folder first (`rm -rf ~/.codex/skills/excalidraw-skill`) then re-copy.

### Install The Skill (Claude Code)

**User-level** (available across all your projects):
```bash
mkdir -p ~/.claude/skills
cp -R skills/excalidraw-skill ~/.claude/skills/excalidraw-skill
```

**Project-level** (scoped to a specific project, can be committed to the repo):
```bash
mkdir -p /path/to/your/project/.claude/skills
cp -R skills/excalidraw-skill /path/to/your/project/.claude/skills/excalidraw-skill
```

Then invoke the skill in Claude Code with `/excalidraw-skill`.

To update an existing installation, remove the old folder first then re-copy.

### Use The Skill Scripts

All scripts respect `EXPRESS_SERVER_URL` (default `http://localhost:3000`) or accept `--url`.

```bash
EXPRESS_SERVER_URL=http://127.0.0.1:3000 node skills/excalidraw-skill/scripts/healthcheck.cjs
EXPRESS_SERVER_URL=http://127.0.0.1:3000 node skills/excalidraw-skill/scripts/export-elements.cjs --out diagram.elements.json
EXPRESS_SERVER_URL=http://127.0.0.1:3000 node skills/excalidraw-skill/scripts/import-elements.cjs --in diagram.elements.json --mode batch
```

### When The Skill Is Useful

- Repository workflow: export elements as JSON, commit it, and re-import later.
- Reliable refactors: clear + re-import in `sync` mode to make canvas match a file.
- Automated smoke tests: create/update/delete a known element to validate a deployment.
- Repeatable diagrams: keep a library of element JSON snippets and import them.

See `skills/excalidraw-skill/SKILL.md` and `skills/excalidraw-skill/references/cheatsheet.md`.

## MCP Tools (26 Total)

| Category | Tools |
|---|---|
| **Element CRUD** | `create_element`, `get_element`, `update_element`, `delete_element`, `query_elements`, `batch_create_elements`, `duplicate_elements` |
| **Layout** | `align_elements`, `distribute_elements`, `group_elements`, `ungroup_elements`, `lock_elements`, `unlock_elements` |
| **Scene Awareness** | `describe_scene`, `get_canvas_screenshot` |
| **File I/O** | `export_scene`, `import_scene`, `export_to_image`, `export_to_excalidraw_url`, `create_from_mermaid` |
| **State Management** | `clear_canvas`, `snapshot_scene`, `restore_snapshot` |
| **Viewport** | `set_viewport` |
| **Design Guide** | `read_diagram_guide` |
| **Resources** | `get_resource` |

Full schemas are discoverable via `tools/list` or in `skills/excalidraw-skill/references/cheatsheet.md`.

## Testing

### Canvas Smoke Test (HTTP)

```bash
curl http://localhost:3000/health
```

### MCP Smoke Test (MCP Inspector)

List tools:
```bash
npx @modelcontextprotocol/inspector --cli \
  -e EXPRESS_SERVER_URL=http://localhost:3000 \
  -e ENABLE_CANVAS_SYNC=true -- \
  node dist/index.js --method tools/list
```

Create a rectangle:
```bash
npx @modelcontextprotocol/inspector --cli \
  -e EXPRESS_SERVER_URL=http://localhost:3000 \
  -e ENABLE_CANVAS_SYNC=true -- \
  node dist/index.js --method tools/call --tool-name create_element \
  --tool-arg type=rectangle --tool-arg x=100 --tool-arg y=100 \
  --tool-arg width=300 --tool-arg height=200
```

### Frontend Screenshots (agent-browser)

If you use `agent-browser` for UI checks:
```bash
agent-browser install
agent-browser open http://127.0.0.1:3000
agent-browser wait --load networkidle
agent-browser screenshot /tmp/canvas.png
```

## Troubleshooting

- Canvas not updating: confirm `EXPRESS_SERVER_URL` points at the running canvas server.
- Updates/deletes fail after batch creation: ensure you are on a build that includes the batch id preservation fix (merged via PR #34).

## Known Issues / TODO

All previously listed bugs have been fixed in v2.0. Remaining items:

- [ ] **Persistent storage**: Elements are stored in-memory — restarting the server clears everything. Use `export_scene` / snapshots as a workaround.
- [ ] **Image export requires a browser**: `export_to_image` and `get_canvas_screenshot` rely on the frontend doing the actual rendering. The canvas UI must be open in a browser.

Contributions welcome!

## Development

```bash
npm run type-check
npm run build
```
