mcp
mcp example from webset
zhkzly
README
mcp
这个是参考:
https://mp.weixin.qq.com/s/ULxokHOn4zVOgiLHf9DQUA,
https://zhuanlan.zhihu.com/p/20222456593
作出一些简单地补充,采用cline 当作client,可以选择gemini作为llm
文中似乎没有特意注明如何使用claude desktop。这里可以选择多种client作为和llm沟通的平台(就是一个界面,也可以自己写)
当前可以选择的client 在llms-full.txt 中有列出来
server 主要是用来生成工具的,工具正如/src/calculate.py,src/datawale.py中展示的,所以一般而言,我们需要定义的就是这个工具(有人进行了开源可以自行选择,比如:https://composio.dev/)
在这里主要展示如何使用client
vscode 中安装Cline 插件,选择合适的模型,如上图
然后选择 mcp servers ,installed ,edit configuration将配置文件添加进去即可
command 这里必须使用绝对路径,相对路径会出现错误
调用工具的时候,应该是类似与首先执行server 使其始终运行,以便之后进行通信调用 类似于:/Users/{username}/.local/bin/uv --directory /Users/{username}... run txt_counter.py
--directory 切换执行目录。
也可以直接运行txt_counter.py,但是需要自己修改端口
client(我没有尝试)
src/mcp_client.py
参考:https://github.com/modelcontextprotocol/python-sdk?tab=readme-ov-file#quickstart
实际上的作用就是类似于一个ui,目的就是和llm进行通信,获取response(比如需要调用的工具,可以参考langchain)
llms-full.txt<br> 官方的说明文档吧(第一个链接中有)
一些使用的简单示例
https://modelcontextprotocol.io/examples
prompts:的结构
有点类似与langchain bind_tools,但是功能更强大
https://modelcontextprotocol.io/docs/concepts/prompts#prompts
Prompts enable servers to define reusable prompt templates and workflows that clients can easily surface to users and LLMs. They provide a powerful way to standardize and share common LLM interactions.
Prompts are designed to be user-controlled , meaning they are exposed from servers to clients with the intention of the user being able to explicitly select them for use.
{
name: string; // Unique identifier for the prompt
description?: string; // Human-readable description
arguments?: [ // Optional list of arguments
{
name: string; // Argument identifier
description?: string; // Argument description
required?: boolean; // Whether argument is required
}
]
}
how to use:
git clone <repo_path>
cd <repo>
安装 uv
https://docs.astral.sh/uv/getting-started/installation/
uv run script.py
上面的指令会自动安装对应的环境到(./.venv)当前文件夹下,实际上在cline中配置mcp server的时候会自己运行uv相关的内容,如果没有环境,会自动根据项目下的
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