How do I install MCP SERVER?
Clone the GitHub repository, create a Python 3.12 virtual environment, activate it, and run `uv pip install -e .` inside the project directory.
@JeanVittory
基本信息
With this MCP, you can debug your application by querying any issue to an LLM using the latest documentation available on the web. We currently support LangChain, LlamaIndex, and OpenAI docs, but you can add any other sources as needed.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server": {
"command": "uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/YOUR/mcp-server-code",
"run",
"src/main.py"
],
"env": {
"SERPER_API_KEY": ""
}
}
}
}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。
MCP SERVER is a Model Context Protocol server that enables queries about any issue using the latest documentation available on the web. It currently supports LangChain, LlamaIndex, and OpenAI documentation, and is designed for developers debugging their applications.
Clone the repository, create a Python 3.12 virtual environment, activate it, and install with uv pip install -e .. Obtain a Serper API key and set it as an environment variable. Configure the MCP client (e.g., Claude Desktop) with the provided JSON snippet pointing to src/main.py. The server is invoked via the MCP client.
Clone the GitHub repository, create a Python 3.12 virtual environment, activate it, and run `uv pip install -e .` inside the project directory.
You need a Serper API key. Set it as the environment variable `SERPER_API_KEY` (generated at serper.dev).
Open the `docs_urls` variable in the constants folder and add the URLs of the documentation you want to reference to that dictionary.
Contact the author at vittory.dev@gmail.com or submit an issue on the GitHub repository.

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