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MCP-Ollama Server

@Sethuram2003

代码仓库

基本信息

分类

AI 与智能体

许可证

Apache-2.0

传输方式

stdio

作者

Sethuram2003

关于 MCP-Ollama Server

Extends Model Context Protocol (MCP) to local LLMs via Ollama, enabling Claude-like tool use (files, web, email, GitHub, AI images) while keeping data private. Modular Python servers for on-prem AI. #LocalAI #MCP #Ollama

MCP-Ollama Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "MCP-ollama_server": {
      "command": "uv",
      "args": [
        "run",
        "client.py",
        "../file_system/file_system.py"
      ]
    }
  }
}

MCP-Ollama Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is 🚀 MCP-Ollama Server?

🚀 MCP-Ollama Server bridges Anthropic's Model Context Protocol (MCP) with local LLMs via Ollama, enabling on-premise AI models with tool capabilities like file system access, calendar integration, web browsing, email, GitHub, and AI image generation while ensuring complete data privacy.

How to use 🚀 MCP-Ollama Server?

Install prerequisites (Python 3.8+, Ollama, Git), clone the repository, and pull a model (e.g., ollama pull llama3). Then navigate to a module directory (e.g., client_mcp/) and run uv run client.py ../file_system/file_system.py to start interacting with the agent.

Key features of 🚀 MCP-Ollama Server

  • 🔒 Complete data privacy – all computations run locally via Ollama
  • 🔧 Tool use for local LLMs (file, calendar, and more)
  • 🧩 Modular architecture with independent Python service modules
  • 🔌 Easy integration via simple APIs
  • 🚀 Performance optimized for responsive AI interactions
  • 📦 Containerized deployment with Docker (coming soon)
  • 🧪 Extensive test coverage for reliability

Use cases of 🚀 MCP-Ollama Server

  • Enterprise security & compliance (legal, healthcare, financial institutions)
  • Developer productivity (code generation, automated documentation, git integration)
  • Personal knowledge management (document processing, calendar management, content generation)

常见问题

1

How does this differ from using cloud-based AI assistants?

MCP-Ollama Server runs entirely on your local infrastructure, ensuring complete data privacy and eliminating dependence on external APIs.

2

What models are supported?

Any model compatible with Ollama can be used. For best results, we recommend Llama 3, Mistral, or other recent open models with at least 7B parameters.

3

How can I extend the system with new capabilities?

Follow the modular architecture pattern to create new service modules. See the Extension Guide for details.

4

What are the system requirements?

Requirements depend on the Ollama model you choose. For basic functionality, we recommend at least 16GB RAM and a modern multi-core CPU.

评论

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