MaplePrimes Announcement

Over the past year, I have spent a lot of time talking to educators, researchers, and engineers about AI. The feeling is almost universal: it is impressive, it is helpful, but you should absolutely not trust it with your math even if it sounds confident.

That tension between how capable AI feels and how accurate it actually is has been on my mind for months. AI is not going away. The challenge now is figuring out how to make it reliable.

That is where Maple MCP comes in.

Maple MCP (Model Context Protocol) connects large language models like ChatGPT, Claude, Cohere, and Perplexity to Maple’s world-class math engine.

When your AI encounters math, your AI can turn to Maple to handle the computation so the results are ones you can actually trust.

It is a simple idea, but an important one: Maple does the math and the AI does the talking. Instead of guessing, the AI can be directed to call on Maple whenever accuracy matters.

Model Context Protocol (MCP) is an emerging open standard that allows AI systems to connect to external tools and data sources. It gives language models a structured way to request computations, pass inputs, and receive reliable outputs, rather than trying to predict everything in text form.

Here is a high-level view of how MCP fits into the broader ecosystem:

MCP Architecture Diagram

Figure 1. High-level architecture of the Model Context Protocol (MCP)
Source: modelcontextprotocol.io

MCP lets an AI system connect securely to specialized services, like Maple, that provide capabilities the model does not have on its own.

If you want to learn more about the MCP standard, the documentation is a great starting point: Model Context Protocol documentation

Here is a glimpse of what happens when Maple joins the conversation:

Examples of Maple MCP in action

Figure 2. Examples of Maple MCP in action

Depending on the prompt, Maple MCP can evaluate expressions symbolically or numerically, execute Maple code, expand or factor expressions, integrate or solve equations, and even generate interactive visualizations. If you ask for an exploration or an activity, it can create a Maple Learn document with the parameters and sliders already in place.

As an example of how this plays out in practice, I asked Maple MCP:

“I'd like to create an interactive math activity in Maple that allows my students to explore the tangent of a line for the function f(x) = sin(x) + 0.5x for various values of x.”

It generated a complete Maple Learn activity that was ready to use and share. You can open the interactive version here: interactive tangent line activity .

In full disclosure, I did have to go back and forth a bit to get the exact results I wanted, mostly because my prompt wasn’t very specific, but the process was smooth, and I know it will only get better over time.

What is exciting is that this does not replace the LLM; it complements it. The model still explains, reasons, and interacts naturally. Maple simply steps in to do the math—the part AI cannot reliably do on its own.

We have opened the Maple MCP public beta, and I would love for you to try it.

Sign up today and we will send you everything you need to get started!

Featured Post

The recordings from Maple Conference presentations, including the workshops, are now available on the conference website.

Thank you to all those who attended or presented, you made the conference a great success!
We hope to see you all again next year.

 

Kaska Kowalska
Contributed Program Co-Chair

Featured Post

The Autumn Issue is now up, at mapletransactions.org

This issue contains two Featured Contributions; a short but very interesting one by Gilbert Labelle on a topic very dear to my own heart, and a longer and also very interesting one by Wadim Zudilin.  I asked Doron Zeilberger about Wadim's paper, and he said "this is a true gem with lots of insight and making connections between different approaches."

The "Editor's Corner" paper is a little different, this time.  This paper is largely the work of my co-author, Michelle Hatzel, extracted and revised from her Masters' thesis which she defended successfully this past August.  I hope that you find it as interesting as I did.

 

We have three refereed contributions, a contribution on the use of Maple Learn in teaching, and a little note on my design of the 2026 Calendar for my upcoming SIAM book with Nic Fillion, as well.  All the images for the calendar were generated in Maple (as were most of the images in the book).

It's been fun to put this issue together (with an enormous amount of help from Michelle) and I hope that you enjoy reading it.

I would also like to thank the Associate Editors who handled the refereeing: Dhavide Aruliah, David Jeffrey, and Viktor Levandovskyy.



how to solve coupled pde

Maple 2025 asked by KIRAN SAJJ... 50 December 08