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Add mcp-turboquant to Data Science Tools

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LLM quantization MCP server. GGUF/GPTQ/AWQ via tool call.
Recommend settings, evaluate quality, push to HF Hub.
MIT licensed, Glama verified.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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ShipItAndPray
2026-04-02 01:28:41 -05:00
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@@ -995,6 +995,7 @@ Integrations and tools designed to simplify data exploration, analysis and enhan
- [phuongrealmax/code-guardian](https://github.com/phuongrealmax/code-guardian) 📇 🏠 - AI-powered code refactor engine with 80+ MCP tools for code analysis, hotspot detection, complexity metrics, persistent memory, and automated refactoring plans.
- [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.
- [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.
- [ShipItAndPray/mcp-turboquant](https://github.com/ShipItAndPray/mcp-turboquant) [![ShipItAndPray/mcp-turboquant MCP server](https://glama.ai/mcp/servers/ShipItAndPray/mcp-turboquant/badges/score.svg)](https://glama.ai/mcp/servers/ShipItAndPray/mcp-turboquant) 📇 🏠 🍎 🪟 🐧 - LLM quantization via tool call. Convert models to GGUF, GPTQ, and AWQ formats. Recommend optimal quant settings, evaluate quality, and push to Hugging Face Hub.
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- [subelsky/bundler_mcp](https://github.com/subelsky/bundler_mcp) 💎 🏠 - Enables agents to query local information about dependencies in a Ruby project's `Gemfile`.
- [zcaceres/markdownify-mcp](https://github.com/zcaceres/markdownify-mcp) 📇 🏠 - An MCP server to convert almost any file or web content into Markdown