JSON Canvas MCP Server

Name: JSON Canvas MCP Server
Author: Cam10001110101

@Cam10001110101

リポジトリ

JSON Canvas MCP Server について

概要はまだありません

#jsoncanvas #mcp-server #canvas-tools

基本情報

カテゴリ

メモリとナレッジ

ライセンス

MIT

ランタイム

html

トランスポート

stdio

公開者

Cam10001110101

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-server-obsidian-jsoncanvas": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "mcp/jsoncanvas",
        "."
      ]
    }
  }
}

ツール

Create a canvas from `nodes` (and optional `edges`) and write it to a

Validate canvas data against the JSON Canvas 1.0 specification.

Read a stored `.canvas` file and return its nodes and edges.

List the `.canvas` files available in `OUTPUT_PATH`.

Add, update, and/or remove nodes and edges on a stored canvas in one

Export a stored canvas to another format.

Case-insensitive substring search across stored canvases.

概要

What is JSON Canvas MCP Server?

An MCP (Model Context Protocol) server for working with JSON Canvas files (.canvas), the open infinite-canvas format used by Obsidian. It allows an MCP client to create, validate, read, list, edit, export, and search canvas files. Built on the mcp Python SDK (>=1.27) and runs over stdio or Streamable HTTP transport.

How to use JSON Canvas MCP Server?

Install via Docker or uv. Configure the server with environment variables (e.g., OUTPUT_PATH). Invoke with mcp-server-jsoncanvas. Integrate with Claude Desktop by adding a stanza to claude_desktop_config.json (see examples for Docker and uv). The server can also be used as a Python library via the jsoncanvas package.

Key features of JSON Canvas MCP Server

Five tools: create_canvas, validate_canvas, read_canvas, list_canvases, edit_canvas, export_canvas, search_canvases
Interactive canvas viewer (MCP Apps UI) for UI-capable hosts
Export canvases to Markdown (edge-ordered outline) or SVG (vector image)
Atomic edit operations (add/update/remove nodes and edges)
Case-insensitive substring search across stored canvases

Use cases of JSON Canvas MCP Server

Creating and saving structured infinite canvas files from AI conversations
Validating canvas data against the JSON Canvas 1.0 specification
Reading and editing existing canvases programmatically
Searching across multiple canvases for specific content
Exporting canvases as Markdown outlines or SVG images

FAQ from JSON Canvas MCP Server

What transports does the server support?

It supports stdio (default) and Streamable HTTP. Set MCP_TRANSPORT environment variable or use the --transport streamable-http command-line flag.

How do I configure the server?

Set the OUTPUT_PATH environment variable to the directory where .canvas files are stored (default ./output). For HTTP transport, optionally set MCP_HOST, MCP_PORT, and MCP_CORS_ORIGINS.

Can I use the server as a Python library?

Yes. The jsoncanvas package can be imported directly to create Canvas objects, add nodes/edges, and serialize to JSON.

Is the HTTP transport secure?

No. It is unauthenticated and intended for local use only. The server binds to 127.0.0.1 by default and rejects non-localhost Host/Origin headers. For remote access, front it with an authenticating reverse proxy.

Does the interactive canvas viewer require a UI?

Only MCP hosts that support the MCP Apps UI extension can render the interactive canvas viewer. Text-only clients receive canvas data as structured output.

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