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使用 Ollama 的本地 MCP 服务器

一个本地 Python 项目,将 Ollama 语言模型连接到 MCP 服务器。该模型可以发现服务器的工具,决定何时调用其中一个,接收结果,并生成简洁的最终响应。

flowchart TD
    U["User question"] --> C["Python MCP client"]
    C --> O["Ollama llama3.2:3b"]
    O --> C
    C --> S["Local MCP server"]
    S --> D["Student JSON data"]

可用工具

工具

用途

add_numbers

将两个显式提供的数字相加

get_student_info

返回内置的演示学生档案

search_students

按姓名和请求的字段在 files/students.json 中搜索

Related MCP server: custom-mcp-server

要求

  • Python 3.11+

  • 已安装并正在运行的 Ollama

  • Ollama 模型 llama3.2:3b

Windows 设置

python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt
ollama pull llama3.2:3b
python client.py

客户端通过当前使用的 Python 解释器自动启动 server.py。您无需在单独的终端中启动服务器。

示例问题

  • What is 10 + 20?

  • Tell me about Pranay.

  • Where is Ananya studying?

  • What is Saranya studying?

项目结构

mcp-server/
├── client.py
├── server.py
├── files/
│   └── students.json
├── tests/
│   └── test_server.py
└── requirements.txt

工具结果修复

Ollama 期望工具结果消息中包含已执行的 tool_name。客户端会包含此字段,并将可用的工具定义传入后续调用,从而使模型能够在 MCP 工具运行后生成最终响应。

数据说明

files/students.json 是演示数据。在公开或生产环境中使用此项目之前,请将其替换为虚构或已获同意使用的数据。

F
license - not found
Not graded
quality - not tested
C
maintenance

Maintenance

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