Jupyter-MCP, PyCharm-MCP, GitHub-MCP, Docker-MCP, SQL-MCP, Excel-MCP, PowerPoint-MCP
Model Context Protocol (MCP) is heating up fast. The internet is filled with use cases around MCP servers, and they are truly the AI agents 2.0
A number of MCP servers have been open-sourced by a number of tech firms and individual contributors. Here in this post, I am helping you out by suggesting the best MCP servers that are meant for data scientists or data analysts.
In case you don’t know what MCP Servers are
https://medium.com/media/ccbb1df1b6576f60c02a7f3a4696a26e/href
So let’s get started
Jupyter-MCP
Jupyter Notebooks are the bread and butter for data scientists.
https://medium.com/media/2f9884bc97deff4bb4c818788a463fc3/href
This server makes it easy for data scientists to use Jupyter Notebooks with AI help. You can write code, create notes, and analyse data just by giving simple instructions. It’s great for testing ideas, making charts, and sharing work with others, all in one place.
PyCharm-MCP
data scientists find it very hard to write production-ready code, but not now.
https://medium.com/media/53a59ea0f442d9e96748bc340a918af0/href
PyCharm-MCP connects the PyCharm coding tool with AI, helping data scientists write and fix code faster. You can ask the AI to explain code or handle boring tasks, which is perfect for big data projects. It keeps everything organised so you can focus on building models.
GitHub-MCP
What happens once development is done? Now GitHub comes into action
https://medium.com/media/e1d347ab11f6eedead2da8d0ed4b9154/href
GitHub-MCP is a lifesaver for data scientists working on team projects. It lets you use AI to manage code storage, track changes, or summarize updates with simple commands. This saves time and makes it easier to collaborate on data science work.
Docker-MCP
With the current wave of GenAI, Python packages are ever-evolving, and you need to maintain your environment consistency using Docker.
https://medium.com/media/55dab40a05d94a9e15a0d39706b9fc7e/href
Docker-MCP helps data scientists set up consistent work environments using AI. You can ask it to start tools for experiments or handle big data tasks without worrying about setup issues. It’s like having a virtual workspace that’s always ready to go.
SQL-MCP
Data Analysis? Any data pull request? SQL is the solution.
https://medium.com/media/39fd8d7cae85d2a3d7b4a7b10e82f323/href
SQL-MCP lets data scientists talk to databases in plain English to pull out data. It’s super helpful for exploring large datasets without writing complex code. This makes it easier to find insights and make decisions based on data.
Excel-MCP
Whether you are a software developer or data scientist, you can’t escape Excel.
https://medium.com/media/2080452a024c66459a01d3a5f9564f68/href
Excel-MCP is great for data scientists who work with spreadsheets. It uses AI to clean data, make charts, or automate tasks in Excel. This saves time on routine work and helps turn raw data into clear reports.
PowerPoint-MCP
When data scientists meet business, they need presentations
https://medium.com/media/94052f8985c0e0800674c3d9f594fd58/href
PowerPoint-MCP helps data scientists create presentations quickly. You can tell the AI what you need, and it builds slides with your findings, nicely formatted. It’s a huge time-saver for sharing results with bosses or clients.
With this, it’s a wrap. I hope you like this particular blog post and you try out all these amazing MCP servers.
https://medium.com/media/ab7be2479b73fddcfe604693aca22c12/href
Best MCP Servers for Data Scientists was originally published in Data Science in Your Pocket on Medium, where people are continuing the conversation by highlighting and responding to this story.
