# mcp-turboquant

> mcp-turboquant — shipitandpray-mcp-turboquant. Use this tool when you need to compress large language models into more efficient formats like GGUF, GPTQ, or AWQ, solving problems of model size and inference speed. It takes in a full-precision model as input and outputs a quantized model, providing a streamlined interface for model compression. Ideal for use cases where model deployment requires reduced memory footprint and faster inference times.

Canonical page: https://skillsregistry.net/skills/shipitandpray-mcp-turboquant  
JSON: https://api.skillsregistry.net/v1/skills/shipitandpray-mcp-turboquant

## Description

MCP server for LLM quantization. Compress any model to GGUF/GPTQ/AWQ in one tool call. First MCP server for model compression.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/ShipItAndPray/mcp-turboquant)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "shipitandpray-mcp-turboquant"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/shipitandpray-mcp-turboquant` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/shipitandpray-mcp-turboquant/pull`

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