Data Science Tools

🐍 🏠 - connects Jupyter Notebook to Claude AI, allowing Claude to directly interact with and control Jupyter Notebooks.

🏎️ 🏠 - 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.

🐍 🏠 - Create, read, validate, and save Stella system dynamics models (.stmx files in XMILE format) for scientific simulation and modeling.

🐍 🏠 - 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.

[glama](https://glama.ai/mcp/servers/WaveGuard) 🐍 ☁️ 🍎 🪟 🐧 - Physics-based anomaly detection via MCP. Uses Klein-Gordon wave equations on GPU to detect anomalies with high precision (avg 0.90). 9 tools: scan, fingerprint, compare, token risk, wallet profiling, volume check, price manipulation detection.

🎖️ 🐍 ☁️ 🪟 🐧 🍎 - Create, manage, and automate Label Studio projects, tasks, and predictions for data labeling workflows.

🎖️ 🐍 🏠 - Tools and templates to create validated and maintainable data charts and dashboards.

🏠 🍎 🪟 🐧 - Model Context Protocol for R: enables AI agents to participate in interactive live R sessions.

📇 🏠 - AI-powered code refactor engine with 80+ MCP tools for code analysis, hotspot detection, complexity metrics, persistent memory, and automated refactoring plans.

🐍 - 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.

💎 🏠 - Enables agents to query local information about dependencies in a Ruby project's `Gemfile`.