# local-model-suitability-mcp

> local-model-suitability-mcp — ojaskord-local-model-suitability-mcp. Use this tool when you need to assess the suitability of local models for specific use cases, solving problems related to model deployment and optimization. It takes in model parameters and performance metrics as inputs and outputs a suitability score, helping you determine the best model for your needs. Ideal for use in machine learning pipelines, particularly when deploying models to local environments via git.

Canonical page: https://skillsregistry.net/skills/ojaskord-local-model-suitability-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ojaskord-local-model-suitability-mcp

## Trust

- **Trust score (0–1):** 0.49
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/OjasKord/local-model-suitability-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": "ojaskord-local-model-suitability-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ojaskord-local-model-suitability-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ojaskord-local-model-suitability-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