JSON Canvas MCP Server

@Cam10001110101

代码仓库

基本信息

分类

记忆与知识

许可证

MIT

传输方式

stdio

作者

Cam10001110101

关于 JSON Canvas MCP Server

暂无概览

#jsoncanvas#mcp-server#canvas-tools

JSON Canvas MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

JSON Canvas MCP Server 工具

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.

概览

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

常见问题

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.