# mcp-client-for-ollama

> mcp-client-for-ollama — jonigl-mcp-client-for-ollama. Use this tool when you need to interact with MCP servers using Ollama, to streamline development workflows with local large language models (LLMs) and leverage features like model switching, streaming responses, and human-in-the-loop capabilities. It provides a text-based user interface for efficient communication with MCP servers, allowing for customized prompts and saved preferences. Ideal for developers working with LLMs who require a flexible and feature-rich client for testing and integration purposes.

Canonical page: https://skillsregistry.net/skills/jonigl-mcp-client-for-ollama  
JSON: https://api.skillsregistry.net/v1/skills/jonigl-mcp-client-for-ollama

## Description

Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved preferences.

## Trust

- **Trust score (0–1):** 0.71
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/jonigl/mcp-client-for-ollama)

## 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": "jonigl-mcp-client-for-ollama"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jonigl-mcp-client-for-ollama` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jonigl-mcp-client-for-ollama/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