Is AI technology coming

vu m. shared this question 55 days ago
Discussion Open

I want to know if the delay in releasing the new version is because the development team is integrating AI into Mind Manager. Thank!

Replies (1)

photo
3

There is already AI integration for MindManager.

See filelinker admin.


https://youtu.be/1Ez-3GpKUgM?si=WGd0jLiYcUHjJuqB

photo
3

... and support for AI Agents has just been announced

photo
1

could you please share the link of the announcement ?
Thanks a lot

photo
1

I received a newsletter about updates to the MindManager App. The subscription page is here:
https://filelinkerenterprise.com/en/newsletter-anmeldung/

photo
1

Thanks Nick

photo
1

That's AI to create text and then import it into MM, AI to analyze available maps is probably a better idea

photo
1

Why?

photo
4

Where do I use MindManager or mind maps?

- WPS with documented information on the project process, including comments on changes

- Recording new findings

- Preparing training courses and seminars

- Meeting minutes

- Training materials for participants

Actually, I hardly use any other tools ;-)

I work with various AI tools on a daily basis.

- Evaluation of WPS in projects

- Analysis of documents and consolidation of content

- Joint concept work

- Analysis of sources on a topic

This is just a small excerpt from my daily work with the various AI tools.

I am aware of the advantage of creating my own mind maps, and I use them too.

But it's not just about copying ChatGPT into a mind map, for example. In some cases, I create an OPML file and import it.

https://www.youtube.com/watch?v=nW6QqRaiGrg

For those who don't know yet: NotebookLM ! It is currently my second favourite tool ;-)

The video shows the status as of 25 March. A lot has happened since then. https://www.youtube.com/watch?v=nW6QqRaiGrg

photo
2

Re: using AI to analyse maps
If the map is a well structured outline, then you can already export it to Word and submit it into AI. But a well-structured visual map is or should be a better summary than AI-generated linear text. If the map is a genuine mind map, then more than half the meaning is in the author's head, not on the page. Connections in a mind map are obvious to the author, but ambiguous to other people. This is very difficult for authors to see. AI will need to guess at the associations and intentions of the map in order to analyse it. An export to linear text will not capture the meaning of a mind map.

photo
1

Hi all, I’m glad to see the conversation shifting toward how MindManager should integrate with AI. Here are a few technical insights and warnings based on my experience:

1. A Note on FileLinker
While FileLinker is a common suggestion, be aware of a specific "feature": if your LLM output contains numbered lists (1, 2, 3...), the tool may strip those numbers AND TEXT/content entirely. The developers have confirmed this is intentional, so double-check your formatting after importing.

2. MCP & Python Library Performance Using MCP (Model Context Protocol) tools via Python is a powerhouse method for AI integration, but current libraries have limitations:

  • The mindm library: While useful, it seems optimized for specific workflows (like transforming .mmap files for Memraid). the mindm-mcp mainly on read; i extended it to write using the mindm python library, but...
  • Latency: Fetching a selected topic currently takes nearly a minute. Using the native MM20 API directly should reduce this to 5–10 seconds.
  • Future Goal: I hope to eventually bypass the existing library and wrap MCP tools directly from the API for better performance.

3. API Documentation & Context7 Tools like Context7 provide manual APIs to LLMs. It would be a significant win if Alludo collaborated with them to index the MM20 API, making it easier for AI to understand and interact with MindManager structures.

Pro-Tip for MM20 Users: If you are still using MM20, download and backup the API documentation locally now. Alludo is phasing out support, and once it’s removed from their servers, it will be much harder to build custom AI tools.

these concise english are from gemini.

photo
1

hi @nick i think one can select the top of the tree of topics, and then copy and paste is enough, why need to export first to word? one can use "paste as text" so the output is plain text, otherwise one is pasting a graphics. "paste as text" have a windows 10 shortcut -- seems need microsoft's free powertoys?

1. Open **PowerToys Settings**

2. Go to **Advanced Paste** (or **Paste as plain text**)

3. Turn it **On**

4. Set/confirm the hotkey as **Win + Ctrl + V**

5. Use it: **Copy (Ctrl + C)** → click the target field → press **Win + Ctrl + V** to paste **plain text**

photo
1

btw, .md works better with LLMs. so i personally use macros to export the .mmap automatically into .md, in the same folder.

then you LLM tools could work on the .md for analysis.


if one want information flow in the other direction, then the MCP server is for you... to contribute.

the current mindm-mcp server is ok to read, but slow as stated above.

one have to re-write the read functions using the mm20 api and then add the write functions...

photo
2

Copying and pasting the central topic of a map will copy only the topic texts. Going via a Word export will include topic notes, topic marker legends, and relationships, which AI may be able to usefully interpret.

photo
1

i am sure a macro / addon could make it "2 buttons away" as the "copy/past as text" method instead of a chain of several actions? thanks

photo
1

heard from author of mindm-mcp library, that he made this into using claude SKILLs.

looks like this solve MCP's resources eat up, will help to blend in the LLM into mindmanager workflow.

i have try yet and the mindm-mcp library is still mainly for reading from .mmap, not write into.

Still need sometime to finish the write part (the mindm-20plus library) and either use COM? for faster action or skills.

photo
Leave a Comment
 
Attach a file