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Merge pull request #12405 from mrnh/add-rigor-mcp

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Add rigor to Data Science Tools
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Frank Fiegel
2026-09-06 21:18:59 -06:00
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@@ -1618,6 +1618,7 @@ Integrations and tools designed to simplify data exploration, analysis and enhan
- [leap-laboratories/discovery-engine](https://github.com/leap-laboratories/discovery-engine) [![leap-laboratories/discovery-engine MCP server](https://glama.ai/mcp/servers/leap-laboratories/discovery-engine/badges/score.svg)](https://glama.ai/mcp/servers/leap-laboratories/discovery-engine) 🐍 ☁️ - Superhuman exploratory data analysis that finds the feature interactions and subgroup effects that LLMs and manual exploration miss — with p-values, effect sizes, and literature citations. Data goes in, validated insights come out. Free for public data. - [leap-laboratories/discovery-engine](https://github.com/leap-laboratories/discovery-engine) [![leap-laboratories/discovery-engine MCP server](https://glama.ai/mcp/servers/leap-laboratories/discovery-engine/badges/score.svg)](https://glama.ai/mcp/servers/leap-laboratories/discovery-engine) 🐍 ☁️ - Superhuman exploratory data analysis that finds the feature interactions and subgroup effects that LLMs and manual exploration miss — with p-values, effect sizes, and literature citations. Data goes in, validated insights come out. Free for public data.
- [lihtness/gnomon-mcp](https://github.com/lihtness/gnomon-mcp) [![lihtness/gnomon-mcp MCP server](https://glama.ai/mcp/servers/lihtness/gnomon-mcp/badges/score.svg)](https://glama.ai/mcp/servers/lihtness/gnomon-mcp) 🐍 🏠 🍎 🪟 🐧 - Deterministic batch tools so LLM agents stop next-token-guessing dates and math. Rich `now()` snapshot (18 fields), `calendar(ops)` batch dispatcher (diff/until/since/add/weekday/business_days, natural-language parsing), `calc(expressions)` Python eval with math+stats pre-loaded, and Pint-based unit conversion. One wiring for dates + math + units. Listed in the official MCP Server Registry. `uvx gnomon-mcp`. - [lihtness/gnomon-mcp](https://github.com/lihtness/gnomon-mcp) [![lihtness/gnomon-mcp MCP server](https://glama.ai/mcp/servers/lihtness/gnomon-mcp/badges/score.svg)](https://glama.ai/mcp/servers/lihtness/gnomon-mcp) 🐍 🏠 🍎 🪟 🐧 - Deterministic batch tools so LLM agents stop next-token-guessing dates and math. Rich `now()` snapshot (18 fields), `calendar(ops)` batch dispatcher (diff/until/since/add/weekday/business_days, natural-language parsing), `calc(expressions)` Python eval with math+stats pre-loaded, and Pint-based unit conversion. One wiring for dates + math + units. Listed in the official MCP Server Registry. `uvx gnomon-mcp`.
- [mckinsey/vizro-mcp](https://github.com/mckinsey/vizro/tree/main/vizro-mcp) 🎖️ 🐍 🏠 - Tools and templates to create validated and maintainable data charts and dashboards. - [mckinsey/vizro-mcp](https://github.com/mckinsey/vizro/tree/main/vizro-mcp) 🎖️ 🐍 🏠 - Tools and templates to create validated and maintainable data charts and dashboards.
- [mrnh/rigor](https://github.com/mrnh/rigor) [![mrnh/rigor MCP server](https://glama.ai/mcp/servers/mrnh/rigor/badges/score.svg)](https://glama.ai/mcp/servers/mrnh/rigor) 🐍 🏠 🍎 🪟 🐧 - Classical hypothesis testing, effect sizes, power/sample-size, and multiple-comparisons correction, computed from scratch and returned as a cited, assumption-checked answer instead of a number recalled from training data. `uvx rigor-mcp`.
- [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/). - [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/).
- [Whatsonyourmind/oraclaw](https://github.com/Whatsonyourmind/oraclaw) [![Whatsonyourmind/oraclaw MCP server](https://glama.ai/mcp/servers/Whatsonyourmind/oraclaw/badges/score.svg)](https://glama.ai/mcp/servers/Whatsonyourmind/oraclaw) 📇 ☁️ 🏠 🍎 🪟 🐧 - Decision intelligence MCP server with 19 algorithms (bandits, Monte Carlo, constraint optimization, forecasting, anomaly detection, risk analysis, graph algorithms), 28 MCP tools. Install via `npx -y @oraclaw/mcp-server`. - [Whatsonyourmind/oraclaw](https://github.com/Whatsonyourmind/oraclaw) [![Whatsonyourmind/oraclaw MCP server](https://glama.ai/mcp/servers/Whatsonyourmind/oraclaw/badges/score.svg)](https://glama.ai/mcp/servers/Whatsonyourmind/oraclaw) 📇 ☁️ 🏠 🍎 🪟 🐧 - Decision intelligence MCP server with 19 algorithms (bandits, Monte Carlo, constraint optimization, forecasting, anomaly detection, risk analysis, graph algorithms), 28 MCP tools. Install via `npx -y @oraclaw/mcp-server`.
- [playidea-lab/pcq](https://github.com/playidea-lab/pcq) [![playidea-lab/pcq MCP server](https://glama.ai/mcp/servers/playidea-lab/pcq/badges/score.svg)](https://glama.ai/mcp/servers/playidea-lab/pcq) 🐍 🏠 🍎 🪟 🐧 - Agent-operable ML experiment contract (cq.yaml + JSON contracts) with a built-in MCP server exposing 14 tools (resolve/inspect/run/validate/describe/compare/lineage) for running, validating, and tracing experiments across any framework (PyTorch / HF Trainer / Lightning / sklearn / XGBoost). Apache-2.0. - [playidea-lab/pcq](https://github.com/playidea-lab/pcq) [![playidea-lab/pcq MCP server](https://glama.ai/mcp/servers/playidea-lab/pcq/badges/score.svg)](https://glama.ai/mcp/servers/playidea-lab/pcq) 🐍 🏠 🍎 🪟 🐧 - Agent-operable ML experiment contract (cq.yaml + JSON contracts) with a built-in MCP server exposing 14 tools (resolve/inspect/run/validate/describe/compare/lineage) for running, validating, and tracing experiments across any framework (PyTorch / HF Trainer / Lightning / sklearn / XGBoost). Apache-2.0.