JSON Canvas MCP Server
A server for creating, modifying, validating, and exporting JSON Canvas files, a format for infinite canvas data.
JSON Canvas MCP Server
A Model Context Protocol (MCP) server implementation that provides tools for working with JSON Canvas files according to the official specification. This server enables creating, modifying, and validating infinite canvas data structures.
Overview
The JSON Canvas MCP server provides a complete implementation of the JSON Canvas 1.0 specification, enabling:
- Creation and manipulation of infinite canvas data
- Support for all node types (text, file, link, group)
- Edge connections with styling and labels
- Validation against the specification
- Configurable output paths
Components
Resources
The server exposes the following resources:
canvas://schema: JSON Schema for validating canvas filescanvas://examples: Example canvas files demonstrating different featurescanvas://templates: Templates for creating new canvases
Tools
Node Operations
-
create_node
- Create a new node of any supported type
- Input:
type(string): Node type ("text", "file", "link", "group")properties(object): Node-specific properties- Common:
id,x,y,width,height,color - Type-specific:
text,file,url, etc.
- Common:
- Returns: Created node object
-
update_node
- Update an existing node's properties
- Input:
id(string): Node ID to updateproperties(object): Properties to update
- Returns: Updated node object
-
delete_node
- Remove a node and its connected edges
- Input:
id(string): Node ID to delete
- Returns: Success confirmation
Edge Operations
-
create_edge
- Create a new edge between nodes
- Input:
id(string): Unique edge identifierfromNode(string): Source node IDtoNode(string): Target node IDfromSide(optional string): Start side ("top", "right", "bottom", "left")toSide(optional string): End sidecolor(optional string): Edge colorlabel(optional string): Edge label
- Returns: Created edge object
-
update_edge
- Update an existing edge's properties
- Input:
id(string): Edge ID to updateproperties(object): Properties to update
- Returns: Updated edge object
-
delete_edge
- Remove an edge
- Input:
id(string): Edge ID to delete
- Returns: Success confirmation
Canvas Operations
-
validate_canvas
- Validate a canvas against the specification
- Input:
canvas(object): Canvas data to validate
- Returns: Validation results with any errors
-
export_canvas
- Export canvas to different formats
- Input:
format(string): Target format ("json", "svg", "png")canvas(object): Canvas data to export
- Returns: Exported canvas in requested format
Usage with Claude Desktop
Docker
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"jsoncanvas": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-v",
"canvas-data:/data",
"mcp/jsoncanvas"
],
"env": {
"OUTPUT_PATH": "/data/output"
}
}
}
}
UV
{
"mcpServers": {
"jsoncanvas": {
"command": "uv",
"args": [
"--directory",
"/path/to/jsoncanvas",
"run",
"mcp-server-jsoncanvas"
],
"env": {
"OUTPUT_PATH": "./output"
}
}
}
}
Configuration
The server can be configured using environment variables:
OUTPUT_PATH: Directory where canvas files will be saved (default: "./output")FORMAT: Default output format for canvas files (default: "json")
Building
Docker Build
docker build -t mcp/jsoncanvas .
Local Build
# Install uv if not already installed
curl -LsSf https://astral.sh/uv/install.sh | sh
# Create virtual environment and install dependencies
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
uv pip install -e .
# Run tests
pytest
Example Usage
Creating a Canvas
from jsoncanvas import Canvas, TextNode, Edge
# Create nodes
title = TextNode(
id="title",
x=100,
y=100,
width=400,
height=100,
text="# Hello Canvas\n\nThis is a demonstration.",
color="#4285F4"
)
info = TextNode(
id="info",
x=600,
y=100,
width=300,
height=100,
text="More information here",
color="2" # Using preset color
)
# Create canvas
canvas = Canvas()
canvas.add_node(title)
canvas.add_node(info)
# Connect nodes
edge = Edge(
id="edge1",
from_node="title",
to_node="info",
from_side="right",
to_side="left",
label="Connection"
)
canvas.add_edge(edge)
# Save canvas
canvas.save("example.canvas")
License
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
相關伺服器
Kone.vc
贊助Monetize your AI agent with contextual product recommendations
Microsoft Office (PowerPoint & Excel)
Automate Microsoft PowerPoint and Excel on Windows using AI-powered COM automation.
Procesio MCP Server
Interact with the Procesio automation platform API.
Little Irons
Manage your job search directly. List jobs, create applications, add events, run company research, generate templates, and more.
Yuga Planner
AI Task schedule planning with LLamaIndex and Timefold: breaks down a task description and schedules it around an existing calendar
JP Bids MCP
Japanese government procurement bid search and AI analysis via MCP
Calculator MCP Server
Performs basic arithmetic calculations. A TypeScript-based server demonstrating core MCP concepts.
Freshdesk
Integrates with Freshdesk to manage support tickets, contacts, and other customer service operations.
LimeSurvey
Manage surveys and responses in your LimeSurvey instance.
GranolaMCP
An MCP server for accessing and analyzing Granola.ai meeting data.
Productboard MCP Server
Integrates with the Productboard API, offering 49 specialized tools to manage all major Productboard functionalities.