Xmind Generator MCP Server
Xmind ジェネレーター MCP サーバー
Xmindマインドマップを生成するためのMCP(Model Context Protocol)サーバー。このサーバーにより、LLMはMCPプロトコルを介して構造化されたマインドマップを作成できます。
特徴
階層的なトピック構造を持つXmindマインドマップを生成する
トピックのメモ、ラベル、マーカーのサポート
マインドマップをローカルファイルに保存する
Claude Desktop や他の MCP クライアントとの簡単な統合
Related MCP server: MCP Thinking Server
前提条件
Node.js : バージョン18以上が必要です
Xmind : 生成されたマインドマップを開いて編集するには、 Xmindデスクトップ アプリケーションをインストールします。
Claude Desktop : このツールを拡張機能として使用するために必要
Claude Desktopでのセットアップ
オプション1: npxを使用する(推奨)
Claude Desktop 構成ファイルを作成または編集します。
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
次の構成を追加します。
{ "mcpServers": { "xmind-generator": { "command": "npx", "args": ["xmind-generator-mcp"], "env": { "outputPath": "/path/to/save/xmind/files", "autoOpenFile": "false" } } } }Claudeデスクトップを再起動します
会話の中でXmindジェネレータを使い始めましょう
オプション2: ローカルインストール
リポジトリをクローンします。
git clone https://github.com/BangyiZhang/xmind-generator-mcp.git cd xmind-generator-mcp npm install npm run buildClaude Desktop 構成ファイルを作成または編集します。
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
次の構成を追加します。
{ "mcpServers": { "xmind-generator": { "command": "node", "args": ["path/to/xmind-generator-mcp/dist/index.js"], "env": { "outputPath": "/path/to/save/xmind/files", "autoOpenFile": "false" } } } }path/to/xmind-generator-mcpクローンしたプロジェクトの実際のパスに置き換えます。Claudeデスクトップを再起動します
会話の中でXmindジェネレータを使い始めましょう
注: envセクションはオプションです。サーバーの環境変数を設定できます。
outputPath: Xmindファイルが保存されるデフォルトのディレクトリまたはファイルパス。これは、ツール呼び出し時のoutputPathパラメータで上書きできます。autoOpenFile: 生成された Xmind ファイルを自動的に開くかどうかを制御します。自動開きを無効にするには「false」に設定します(デフォルトは「true」)。
利用可能なツール
マインドマップを生成する
トピックの階層構造から Xmind マインド マップを生成します。
パラメータ:
title(文字列): マインドマップのタイトル(ルートトピック)topics(配列): マインドマップに含めるトピックの配列title(文字列): トピックのタイトルref(文字列、オプション): トピックの参照IDnote(文字列, オプション): トピックのメモlabels(文字列の配列、オプション): トピックのラベルmarkers(文字列の配列、オプション):トピックのマーカー(形式:「Category.name」、例:「Arrow.refresh」)children(配列、オプション): 子トピックの配列
relationships(配列、オプション):トピック間の関係の配列outputPath(文字列、オプション): Xmindファイルのカスタム出力パス。環境変数が設定されている場合は、このパスが優先されます。
例
以下はgenerate-mind-mapツールの使用方法の例です。
{
"title": "Project Plan",
"topics": [
{
"title": "Research",
"ref": "topic:research",
"note": "Gather information about the market",
"children": [
{
"title": "Market Analysis",
"labels": ["Priority: High"]
},
{
"title": "Competitor Research",
"markers": ["Task.quarter"]
}
]
},
{
"title": "Development",
"children": [
{
"title": "Frontend",
"markers": ["Arrow.refresh"]
},
{
"title": "Backend"
}
]
}
]
}ライセンス
マサチューセッツ工科大学
Available Tools
1 toolgenerate-mind-mapD
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes | The filename for the XMind file (without path or extension) | |
| outputPath | No | Optional custom output path for the XMind file. If not provided, the file will be created in the temporary directory. | |
| relationships | No | Optional array of relationships between topics | |
| title | Yes | The title of the mind map (root topic) | |
| topics | Yes | Array of topics to include in the mind map |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- First observed
generate-mind-map
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'generate-mind-map' stands alone with a distinct purpose, making it impossible for an agent to misselect between multiple options.
The naming is trivially consistent as there is only one tool. It follows a clear verb_noun pattern ('generate-mind-map'), and with no other tools to compare against, there is no inconsistency in naming conventions.
A single tool is generally too few for a server's purpose, as it limits functionality and may not cover the domain adequately. For a mind map generator, one tool might suffice for basic generation, but it feels thin and could lack features like editing, saving, or retrieving maps, suggesting an under-scoped implementation.
The tool surface is severely incomplete for a mind map domain. With only a generation tool, there are obvious gaps such as no ability to retrieve, update, delete, or list existing mind maps. This will likely cause agent failures when trying to perform full lifecycle operations, as the server does not support basic CRUD functionality.
Maintenance
Related MCP Connectors
Turn outlines and hierarchical notes into interactive mind maps through a hosted remote MCP server.
MCP server for generating rough-draft project plans from natural-language prompts.
MCP server for AI dialogue using various LLM models via AceDataCloud
MCP server for building and testing AI agents with multi-model experimentation and insights.
Related MCP Servers
- AlicenseDqualityDmaintenanceAn MCP server that enables users to generate structured XMind mind maps with hierarchical topics, notes, and labels through natural language. It features automatic file saving to the local Documents folder and can automatically open generated maps in the XMind application.138 npm1MIT
- AlicenseNot gradedqualityDmaintenanceA powerful MCP server that enhances LLMs with advanced sequential thinking capabilities, supporting 19 thinking modes for structured reasoning and complex cognitive tasks.17MIT
- AlicenseBqualityDmaintenanceMCP server that enables LLMs to create and edit draw.io diagrams using high-level intent commands, with automatic layout and styling.413 npm4MIT
- FlicenseAqualityCmaintenanceAn MCP server that lets Claude or ChatGPT read, create, and edit mind maps stored in a GitHub repository, with support for local and HTTP transport.8-