# loco

> loco — ilovepixelart-loco. Use this tool when you need to set up a local server for large language models (LLMs) like Ollama, LM Studio, and llama.cpp, to enable seamless model management and deployment. It solves problems related to local model serving, allowing for efficient testing and development of LLMs. The loco tool takes model configurations as input and outputs a running server instance, ideal for use cases where a self-hosted LLM solution is required.

Canonical page: https://skillsregistry.net/skills/ilovepixelart-loco  
JSON: https://api.skillsregistry.net/v1/skills/ilovepixelart-loco

## Description

MCP server for local LLMs — Ollama, LM Studio, llama.cpp

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/ilovepixelart/loco)

## 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": "ilovepixelart-loco"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ilovepixelart-loco` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ilovepixelart-loco/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