What are the dependencies and runtime requirements?
Python 3.11 or higher and the `uv` package manager are required. The server also needs API keys for OpenAI, HuggingFace, and SerpAPI.
@Hajime-Y
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使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"deep_research": {
"command": "uv",
"args": [
"--directory",
"/YOUR_ABSOLUTE_PATH_TO/deep-research-mcp",
"run",
"deep_research.py"
]
}
}
}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。
Deep_research is an agent-based tool that provides web search and advanced research capabilities. It leverages HuggingFace’s smolagents and is implemented as an MCP (Model Context Protocol) server, designed for users who need automated information gathering from multiple sources.
After cloning the repository, create a virtual environment with uv, install dependencies with uv sync, and set the required environment variables (OPENAI_API_KEY, HF_TOKEN, SERPER_API_KEY) in a .env file. Start the MCP server by running uv run deep_research.py.
Python 3.11 or higher and the `uv` package manager are required. The server also needs API keys for OpenAI, HuggingFace, and SerpAPI.
An OpenAI API key, a HuggingFace token, and a SerpAPI key (sign up at Serper.dev) must be set as environment variables in a `.env` file.
Run `uv run deep_research.py` from the project root after installing dependencies and configuring environment variables.
Key scripts include `text_web_browser.py`, `text_inspector_tool.py`, `visual_qa.py` for image analysis, and `mdconvert.py` for converting files to Markdown.
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