How to: 🧮 <a name="data-science-tools"></a>Data Science Tools
Integrations and tools designed to simplify data exploration, analysis and enhance data science workflows.

- [arrismo/kaggle-mcp](https://github.com/arrismo/kaggle-mcp) 🐍 ☁️ - Connects to Kaggle, ability to download and analyze datasets.
- [avisangle/calculator-server](https://github.com/avisangle/calculator-server) 🏎️ 🏠 - A comprehensive Go-based MCP server for mathematical computations, implementing 13 mathematical tools across basic arithmetic, advanced functions, statistical analysis, unit conversions, and financial calculations.
- [bradleylab/stella-mcp](https://github.com/bradleylab/stella-mcp) 🐍 🏠 - Create, read, validate, and save Stella system dynamics models (.stmx files in XMILE format) for scientific simulation and modeling.
- [ChronulusAI/chronulus-mcp](https://github.com/ChronulusAI/chronulus-mcp) 🐍 ☁️ - Predict anything with Chronulus AI forecasting and prediction agents.
- [DataEval/dingo](https://github.com/DataEval/dingo) 🎖️ 🐍 🏠 🍎 🪟 🐧 - MCP server for the Dingo: a comprehensive data quality evaluation tool. Server Enables interaction with Dingo's rule-based and LLM-based evaluation capabilities and rules&prompts listing.
- [datalayer/jupyter-mcp-server](https://github.com/datalayer/jupyter-mcp-server) 🐍 🏠 - Model Context Protocol (MCP) Server for Jupyter.
- [abhiphile/fermat-mcp](https://github.com/abhiphile/fermat-mcp) 🐍 🏠 🍎 🪟 🐧 - The ultimate math engine unifying SymPy, NumPy & Matplotlib in one powerful server. Perfect for developers & researchers needing symbolic algebra, numerical computing, and data visualization.
- [growthbook/growthbook-mcp](https://github.com/growthbook/growthbook-mcp) 🎖️ 📇 🏠 🪟 🐧 🍎 — Tools for creating and interacting with GrowthBook feature flags and experiments.
- [HumanSignal/label-studio-mcp-server](https://github.com/HumanSignal/label-studio-mcp-server) 🎖️ 🐍 ☁️ 🪟 🐧 🍎 - Create, manage, and automate Label Studio projects, tasks, and predictions for data labeling workflows.
- [jjsantos01/jupyter-notebook-mcp](https://github.com/jjsantos01/jupyter-notebook-mcp) 🐍 🏠 - connects Jupyter Notebook to Claude AI, allowing Claude to directly interact with and control Jupyter Notebooks.
- [kdqed/zaturn](https://github.com/kdqed/zaturn) 🐍 🏠 🪟 🐧 🍎 - Link multiple data sources (SQL, CSV, Parquet, etc.) and ask AI to analyze the data for insights and visualizations.
- [mckinsey/vizro-mcp](https://github.com/mckinsey/vizro/tree/main/vizro-mcp) 🎖️ 🐍 🏠 - Tools and templates to create validated and maintainable data charts and dashboards.
- [optuna/optuna-mcp](https://github.com/optuna/optuna-mcp) 🎖️ 🐍 🏠 🐧 🍎 - Official MCP server enabling seamless orchestration of hyperparameter search and other optimization tasks with [Optuna](https://optuna.org/).
- [pramod/kaggle](https://github.com/KrishnaPramodParupudi/kaggle-mcp-server) 🐍 - This Kaggle MCP Server makes Kaggle more accessible by letting you browse competitions, leaderboards, models, datasets, and kernels directly within MCP, streamlining discovery for data scientists and developers.
- [phisanti/MCPR](https://github.com/phisanti/MCPR) 🏠 🍎 🪟 🐧 - Model Context Protocol for R: enables AI agents to participate in interactive live R sessions.
- [reading-plus-ai/mcp-server-data-exploration](https://github.com/reading-plus-ai/mcp-server-data-exploration) 🐍 ☁️ - Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.
- [subelsky/bundler_mcp](https://github.com/subelsky/bundler_mcp) 💎 🏠 - Enables agents to query local information about dependencies in a Ruby project's `Gemfile`.
- [Bright-L01/networkx-mcp-server](https://github.com/Bright-L01/networkx-mcp-server) 🐍 🏠 - The first NetworkX integration for Model Context Protocol, enabling graph analysis and visualization directly in AI conversations. Supports 13 operations including centrality algorithms, community detection, PageRank, and graph visualization.
- [zcaceres/markdownify-mcp](https://github.com/zcaceres/markdownify-mcp) 📇 🏠 - An MCP server to convert almost any file or web content into Markdown