M

MindMap AI

Create and edit visual mind maps directly from your Claude conversations.

Education & Research
Claude Desktop Config
{
  "mcpServers": {
    "mindmapai": {
      "type": "http",
      "url": "https://mindmapai.app/mcp"
    }
  }
}

MindMap AI is a community MCP server that connects AI assistants like Claude to create and edit visual mind maps directly from your claude conversations. It runs locally on your machine, keeping your data private and giving you full control over the connection. Adding it to your setup expands what Claude can do without any extra coding.

About MindMap AI

MindMap AI is a hosted remote MCP server that enables AI assistants to create and work with visual mind maps directly from conversations.

Users can create new mind maps from topics, brainstorming sessions, notes, research, documents, and connected content. The server can also search and open existing projects, add or edit nodes, move and reorganize branches, delete nodes, create relationship arrows and summaries, apply themes, and update existing maps.

MindMap AI supports Mind Map, Logic Chart, and Org Chart layouts and can export completed maps in supported formats.

The MCP server is hosted remotely at https://mindmapai.app/mcp and uses OAuth 2.1 authentication. Users do not need to install a local server or manage an API key.

It can be used with MCP-compatible AI clients including Claude, ChatGPT, Claude Code, Cursor, VS Code, OpenAI Codex CLI, Windsurf, and other compatible clients.

Who Should Use MindMap AI?

  • 1Extend Claude and other AI assistants with new capabilities
  • 2Automate tasks that previously required manual steps
  • 3Connect your existing tools to an AI workflow
  • 4Reduce repetitive work by letting AI interact with your services

How MindMap AI Compares

✦It runs entirely on your local machine, so no data leaves your environment — important for teams with privacy or compliance requirements.
✦Compared to other Education & Research MCP servers, it focuses on a well-scoped set of capabilities, which keeps the integration lightweight and predictable.

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