tldraw
Draw and visually collaborate with your agents on tldraw's canvas.
Should I use this
Quality & Safety
Findings (2)
- LOWin _exec_callback
- LOWin _get_canvas_state
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"tldraw": {
"url": "https://tldraw-mcp-app.tldraw.workers.dev/mcp"
}
}
}Remote endpoints
https://tldraw-mcp-app.tldraw.workers.dev/mcpstreamable-httphttps://tldraw-mcp-app.tldraw.workers.dev/ssesseWhat it can do
Tool inventory
Tools (6)
🟢search(code)
Search the tldraw Editor API spec by writing JavaScript that receives a `spec` object and returns a result. The spec contains: spec.members (all Editor methods/properties with name, kind, signature, description, category), spec.categories (category names), spec.types.shapes (focused shape type definitions with props), spec.types.shapeTypes (list of all shape type strings), spec.helpers (exec helper functions with descriptions, params, examples). Examples: - Find shape methods: return spec.members.filter(m => m.category === "shapes").map(m => ({ name: m.name, signature: m.signature })) - Get arrow shape props: return spec.types.shapes.find(s => s.shapeType === "arrow") - List all categories: return spec.categories - Find a helper: return spec.helpers.find(h => h.name === "createArrowBetweenShapes")
Input Schema
{
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "JavaScript code that receives `spec` and returns a result. Must use `return` to produce output."
}
},
"required": [
"code"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟡exec(code, canvasId)
Execute JavaScript code on a tldraw canvas. The code runs in the widget with access to the live `editor` instance, helper functions, and normal js. Use the `search` tool first to discover available Editor methods and shape types. Each canvas has a unique `canvasId`. Omit `canvasId` to create a new blank canvas. To edit an existing canvas, pass the `canvasId` that was returned by a previous exec call. Shapes and text grow depending on the amount of text they have. Use clever scripting to ensure there are no unintended overlaps. Examples: - Create a rectangle: editor.createShape({ _type: 'rectangle', shapeId: 'box1', x: 200, y: 120, w: 320, h: 180, text: 'Hello' }) - Connect shapes with an arrow: editor.createShape({ _type: 'arrow', shapeId: 'a1', fromId: 'box1', toId: 'box2', x1: 0, y1: 0, x2: 100, y2: 0 }) - Select and zoom: editor.select('box1'); editor.zoomToSelection() - Read shapes: return editor.getCurrentPageShapes() - Distribute evenly: editor.distributeShapes(editor.getSelectedShapeIds(), 'horizontal') - Box around shapes: boxShapes(['box1', 'box2'], { text: 'Group label', color: 'blue' }) - Stack shapes dynamically: editor.createShape({ _type: 'rectangle', shapeId: 'a', x: 0, y: 0, w: 300, h: 200, text: 'First box\nwith wrapping text' }); const bounds = editor.getShapePageBounds('a'); editor.createShape({ _type: 'rectangle', shapeId: 'b', x: 0, y: bounds.maxY + 20, w: 300, h: 200, text: 'Below first' })
Input Schema
{
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "JavaScript code to execute. Has access to `editor` (tldraw Editor instance) and helper functions."
},
"canvasId": {
"description": "Canvas ID to edit. Omit to create a new blank canvas. Pass a canvasId from a previous exec result to continue editing that canvas.",
"type": "string"
}
},
"required": [
"code"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}⚪_exec_callback(channel, execKey, result, error)
App-only: widget calls this to resolve a pending exec request.
Input Schema
{
"type": "object",
"properties": {
"channel": {
"type": "string"
},
"execKey": {
"type": "string"
},
"result": {
"type": "object",
"properties": {
"success": {
"type": "boolean"
},
"result": {},
"error": {
"type": "string"
},
"canvasId": {
"type": "string"
}
},
"required": [
"success"
]
},
"error": {
"type": "string"
}
},
"required": [
"channel"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢_get_canvas_state(canvasId)
App-only: get the latest checkpoint for a canvas by its canvasId.
Input Schema
{
"type": "object",
"properties": {
"canvasId": {
"type": "string",
"minLength": 1
}
},
"required": [
"canvasId"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢read_checkpoint(checkpointId)
App-only: read shapes from a checkpoint by ID.
Input Schema
{
"type": "object",
"properties": {
"checkpointId": {
"type": "string",
"minLength": 1
}
},
"required": [
"checkpointId"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟡save_checkpoint(checkpointId, shapesJson, assetsJson, bindingsJson, canvasId)
App-only: save shapes to a checkpoint (from user edits). shapesJson and assetsJson must be JSON array strings.
Input Schema
{
"type": "object",
"properties": {
"checkpointId": {
"type": "string",
"minLength": 1
},
"shapesJson": {
"type": "string"
},
"assetsJson": {
"type": "string"
},
"bindingsJson": {
"type": "string"
},
"canvasId": {
"type": "string"
}
},
"required": [
"checkpointId",
"shapesJson"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}Community
Evidence