# ModelFit-MCP

> ModelFit-MCP — dumbodhruvi-modelfit-mcp. Use this tool when you need to optimize AI model performance on specific hardware configurations, solve memory constraints, and streamline model deployment. ModelFit-MCP provides hardware-aware model discovery, memory fitting, and empirical benchmarking, allowing for seamless integration with local model gateways. It is ideal for AI agents requiring efficient model management and swappable local models, with support for git version control.

Canonical page: https://skillsregistry.net/skills/dumbodhruvi-modelfit-mcp  
JSON: https://api.skillsregistry.net/v1/skills/dumbodhruvi-modelfit-mcp

## Description

Hardware-Aware Hugging Face Discovery, Memory Fitting, Empirical Benchmarking & Swappable Local Model Gateway for AI Agents

## Trust

- **Trust score (0–1):** 0.88
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/DumboDhruvi/ModelFit-MCP)

## 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": "dumbodhruvi-modelfit-mcp"
    }
  }
}
```

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

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt