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MCP Client for Ollama (ollmcp)

@jonigl

リポジトリ

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT

トランスポート

stdio

作者

jonigl

MCP Client for Ollama について

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 pre

#open-source#ai#mcp#sse#model-selection#stdio#command-line-tool#terminal-based#pypi-package#tool-management#chat-interface#llm#generative-ai#local-llm#ollama#model-context-protocol#mcp-server#mcp-client

MCP Client for Ollama の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-client-for-ollama": {
      "command": "uv",
      "args": [
        "tool",
        "install",
        "--upgrade",
        "ollmcp"
      ]
    }
  }
}

MCP Client for Ollama のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP Client for Ollama (ollmcp)?

MCP Client for Ollama (ollmcp) is a Python terminal application that connects local Ollama LLMs to one or more Model Context Protocol (MCP) servers. It supports core MCP primitives—tools, prompts, and resources—and is designed for developers building, testing, or exploring MCP-powered workflows with local AI models.

How to use MCP Client for Ollama (ollmcp)?

Install the package via uv tool install --upgrade ollmcp or pip install --upgrade ollmcp. Add an MCP server with ollmcp mcp add <name> -- <command>, then launch the client by running ollmcp. Use /help inside the interactive session for available commands.

Key features of MCP Client for Ollama (ollmcp)

  • Agent Mode with iterative tool execution and configurable loop limits
  • Multi-Server Support and multiple transport types (STDIO, SSE, Streamable HTTP)
  • Human-in-the-Loop (HIL) tool execution for safety
  • Rich terminal interface with streaming responses and fuzzy autocomplete
  • Dynamic model switching and advanced model parameter configuration
  • Server hot-reloading and conversation history management
  • Support for Ollama (default) and OpenAI-compatible LLM providers

Use cases of MCP Client for Ollama (ollmcp)

  • Connect local Ollama models to existing MCP tool servers for automated tasks
  • Prototype and debug MCP servers during development with hot-reloading
  • Run multi-step agent workflows with strict human approval on tool calls
  • Experiment with different LLM providers and model parameters in a single session

よくある質問

1

What are the runtime requirements?

Python 3.11 or newer, Ollama running locally, and the UV package manager (recommended). pip installation is also supported.

2

How do I fix a "Could not find a version that satisfies the requirement ollmcp" error?

This usually means your Python version is older than 3.11. Use `uv tool install --upgrade ollmcp` (uv auto-selects a compatible Python) or install with a Python 3.11+ interpreter.

3

Can I use cloud-hosted models instead of a local Ollama instance?

Yes. Ollama Cloud is supported, and you can also use OpenAI-compatible providers such as OpenAI, OpenRouter, and DeepSeek.

4

What types of MCP servers does ollmcp connect to?

It supports STDIO, SSE, and Streamable HTTP transport types. It can connect to multiple servers simultaneously and automatically discovers existing Claude MCP configurations.

5

How does tool safety work?

Human-in-the-Loop (HIL) mode lets you review and approve tool executions before they run. You can also enable/disable specific tools or entire servers during a chat session.

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