Train-in-Silence

by hlpun · MCP Server · ★ 102

About Train-in-Silence

Train in Silence The first Task-Aware MCP server for LLM fine-tuning. Stop comparing GPU prices. Start training. 中文 You want to fine-tune an LLM. You open Vast.ai, RunPod, AWS, etc. -- a dozen tabs, a dozen pricing models, a dozen different ways to describe a GPU. Which option can run your code, and do so more cheaply and quickly? An hour later you're still in a spreadsheet and haven't written a single line of training code. Train in Silence is the first Task-Aware MCP server for LLM fine-tuning. It doesn't just list prices; it understands your workload.

claude-codecost-optimizationfine-tuninggpu-pricingllmmcpmcp-serverpythonvram-calculator

Quick Facts

Stars102
Forks2
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score68.1929645826075/100
Last Updated2026-06-24
Created2026-04-12
Platformsclaude-code, mcp, python
Est. Tokens~14k

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Frequently Asked Questions

What is Train-in-Silence?

Train-in-Silence is The first Task-Aware MCP server and automated VRAM calculator for LLM fine-tuning. Instantly snipe the cheapest, fastest GPUs across 10+ cloud providers.. It is categorized as a MCP Server with 102 GitHub stars.

What programming language is Train-in-Silence written in?

Train-in-Silence is primarily written in Python. It covers topics such as claude-code, cost-optimization, fine-tuning.

How do I install or use Train-in-Silence?

You can find installation instructions and usage details in the Train-in-Silence GitHub repository at github.com/hlpun/Train-in-Silence. The project has 102 stars and 2 forks, indicating an active community.

What license does Train-in-Silence use?

Train-in-Silence is released under the MIT license, making it free to use and modify according to the license terms.

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