# MCP Local LLM Server

> Use this tool when you need to efficiently process large files, error logs, and codebase searches while minimizing token consumption. The MCP Local LLM Server reduces token usage in Cursor by up to 80% through local processing via Ollama. It accepts large files and logs as input and provides relevant search results as output, making it ideal for optimizing resource-intensive search tasks.

Canonical page: https://skillsregistry.net/skills/iagomussel-mcp-local-llm  
JSON: https://api.skillsregistry.net/v1/skills/iagomussel-mcp-local-llm

## Description

Processes large files, error logs, and codebase searches locally via Ollama to reduce token consumption in Cursor by up to 80%.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ckdknqow8p)
- **Repository:** <https://github.com/iagomussel/mcp-local-llm>

## 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": "iagomussel-mcp-local-llm"
    }
  }
}
```

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