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Mapify MCP Server

npm version License: MIT Model Context Protocol

Transform text, YouTube videos, and web content into beautiful mind maps using AI 🧠✨

The official Mapify Model Context Protocol (MCP) server enables AI assistants like Claude to generate interactive mind maps from various content sources. Built on the standardized MCP architecture, this server provides seamless integration between AI models and Mapify's powerful mind mapping capabilities.


✨ Features

  • 🎯 Multi-Source Mind Mapping: Generate mind maps from text prompts, YouTube videos, websites, and documents

  • 🔍 AI-Powered Search: Automatically search the web for keywords and create comprehensive mind maps from results

  • 🌍 Multi-Language Support: Create mind maps in 15+ languages including English, Chinese, Japanese, Spanish, and more

  • 📸 Visual + Interactive: Get both static images and editable mind map links


Related MCP server: Mind Map MCP

🔑 Getting Your API Key

Before using the Mapify MCP Server, you'll need to obtain your API token from the Mapify platform.

💡 Already have an account? Jump directly to your settings page and skip to Step 3.

Step 1: Create Your Account

Visit mapify.so and sign up for a free account.

Step 1: Sign up for Mapify

Step 2: Access Main Dashboard

After logging in, you'll see the main Mapify dashboard with your mind maps and tools.

Step 2: Mapify main dashboard

Step 3: Open Account Settings

Click on your profile/account menu to access your account settings.

Step 3: Open account settings

Step 4: Generate Your API Token

Navigate to the "API Key" section and generate your API key. Copy and keep it secure!

Step 4: Generate and copy API token

🔒 Security Note: Treat your API key like a password. Never share it publicly or commit it to version control.


🚀 Quick Start

Prerequisites

  • Node.js (v16 or higher)

  • MCP-compatible client (Claude Desktop, VS Code, Cursor, Continue, etc.)

Installation

For Claude Desktop, add this configuration to your ~/.claude/claude_desktop_config.json:

{
  "mcpServers": {
    "mapify": {
      "command": "npx",
      "args": ["-y", "@xmindltd/mapify-mcp-server"],
      "env": {
        "MAPIFY_API_KEY": "your_api_token_here"
      }
    }
  }
}

📖 Usage Examples

Once configured, you can use these tools with your AI assistant:

Text-to-Mind-Map

Create a mind map about "Machine Learning fundamentals"

AI Search to Mind Map

Create a comprehensive mind map for "climate change solutions 2025" by AI Search

YouTube Video Analysis

Generate a mind map from this YouTube video: https://youtube.com/watch?v=example

Website Content Mapping

Create a mind map from the content on https://example.com/article

The AI assistant will automatically:

  1. 🔄 Process your request using the appropriate Mapify tool

  2. 🌐 Search the web for relevant information

  3. 🎨 Generate a beautiful mind map image

  4. 🔗 Provide an editable link for further customization

  5. 📊 Return dimensions and metadata


🛠️ Manual Installation & Development

Local Setup

# Clone the repository
git clone https://github.com/xmindltd/mapify-mcp-server.git
cd mapify-mcp-server

# Install dependencies
pnpm install

# Build the project
pnpm run build

Using Pre-built Binary

{
  "mcpServers": {
    "mapify": {
      "command": "node",
      "args": ["/absolute/path/to/mapify-mcp-server/build/index.js"],
      "env": {
        "MAPIFY_API_KEY": "your_api_token_here"
      }
    }
  }
}

Ready to transform any ideas into visual mind maps? 🚀

Get Started

Available Tools

1 tool
generate_mindmapA

Generate a mind map from various inputs and provide both an image and an editable link

ParametersJSON Schema
NameRequiredDescriptionDefault
promptYesThe prompt to generate the mind map. When mode is website or youtube, the prompt should be a URL without any other text.
modeNoThe mode to generate the mind mapprompt
languageNoThe language of the mind mapen

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses the output (image and editable link) which is helpful, but does not mention behavioral traits such as rate limits, authentication requirements, or potential side effects. The generation nature implies non-destructive behavior, but more detail would improve transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that is concise and front-loaded with the main action. It avoids unnecessary words but could be restructured to list modes or highlight key output features without becoming overly long.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is relatively simple with 3 parameters and no output schema. The description mentions the output (image and editable link) which is useful, but does not explain the format of the link or any return values. For a basic generation tool, it is adequate but could be more complete by specifying what 'editable link' means.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description does not add additional meaning beyond what the schema already provides. The schema itself has clear descriptions for prompt, mode, and language, including instructions for mode-specific prompt usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a mind map from various inputs and provides both an image and an editable link. It specifies both the action (generate) and the resource (mind map) along with the output format, making the purpose highly identifiable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit when-to-use or when-not-to-use guidance. However, since there are no sibling tools, the need is reduced. The description implies usage for creating mind maps but lacks context on prerequisites or alternatives.

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. Dates show when Glama detected each change.

  1. 1 tool updatev1.0.1
    • First observedgenerate_mindmap

TDQS

A3.6/5.0
Disambiguation5/5

Only one tool exists, so there is no risk of confusion or overlap. The tool's purpose is clear and unambiguous.

Naming Consistency5/5

With a single tool, naming consistency is trivially achieved. The name 'generate_mindmap' follows a clear verb_noun pattern.

Tool Count2/5

A single tool is too few for a service claiming to be a mind map server. Even for a minimal generative service, additional operations (e.g., retrieval, editing) are expected, making the surface feel incomplete.

Completeness2/5

The server only supports generating mind maps, lacking any tools for listing, viewing, updating, or deleting previously created maps. This is a significant gap for typical user workflows.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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