Deep_research: Uncover Hidden Insights, Drive Action

Dig deeper, faster. Deep_research empowers data-driven decisions with intuitive tools to uncover hidden insights, cut through noise, and turn complex findings into clear action.

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About Deep_research

What is Deep_research: Uncover Hidden Insights, Drive Action?

Deep_research is a cutting-edge agent-based tool designed to empower users with advanced research capabilities. Built on HuggingFace’s smolagents framework, it functions as an MCP server that combines web search, document analysis, and multimedia processing into a seamless workflow. Think of it as your digital research assistant—capable of sifting through PDFs, scanning YouTube transcripts, and even describing images to unearth actionable insights.

How to Use Deep_research: Uncover Hidden Insights, Drive Action?

Getting started is straightforward. First, clone the repository and set up your environment with Python 3.11+ and the uv package manager. You’ll need API keys for OpenAI, HuggingFace, and Serper (sign up here). After configuring your .env file, launch the server with uv run deep_research.py, and you’re ready to query everything from scholarly articles to visual data.

Deep_research Features

Key Features of Deep_research: Uncover Hidden Insights, Drive Action?

Web & Archive Scouring: Dig deep into search engines and archive sites for up-to-date or historical data.
Document Sherlock: Automatically parse PDFs, extract text, and convert files to Markdown for easy analysis.
Visual Intelligence: Describe images and answer questions about their content using AI-powered tools.
Transcript Treasure Chest: Pull YouTube captions to analyze spoken content at scale.

Use Cases of Deep_research: Uncover Hidden Insights, Drive Action?

Perfect for researchers racing against deadlines or marketers hunting trends, Deep_research shines in scenarios like:

Competitive analysis: Track industry trends via real-time web searches.
Academic aid: Cross-reference journal PDFs and visualize data insights.
Content curation: Extract key points from YouTube videos for quick summaries.
Compliance audits: Scan archived web pages for policy changes.

Deep_research FAQ

FAQ from Deep_research: Uncover Hidden Insights, Drive Action?

“Does it work offline?” Partially—core tools like PDF parsing function without internet, but web-based features require API access.
“Can I customize the agents?” Absolutely! The modular design allows tweaking agent configurations in create_agent.py.
“Help! My server won’t start.” Check your Python version and environment variables first. The text_web_browser.py script can help debug connectivity issues.
“Why use Serper over Google?” Serper’s API offers structured search results optimized for programmatic use, making data extraction smoother.

Content

Deep Research MCP Server

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 server.

This project is based on HuggingFace's open_deep_research example.

Features

Web search and information gathering
PDF and document analysis
Image analysis and description
YouTube transcript retrieval
Archive site search

Requirements

Python 3.11 or higher
uv package manager
The following API keys:
- OpenAI API key
- HuggingFace token
- SerpAPI key

Installation

Clone the repository:

git clone https://github.com/Hajime-Y/deep-research-mcp.git
cd deep-research-mcp

Create a virtual environment and install dependencies:

uv venv
source .venv/bin/activate # For Linux or Mac
# .venv\Scripts\activate # For Windows
uv sync

Environment Variables

Create a .env file in the root directory of the project and set the following environment variables:

OPENAI_API_KEY=your_openai_api_key
HF_TOKEN=your_huggingface_token
SERPER_API_KEY=your_serper_api_key

You can obtain a SERPER_API_KEY by signing up at Serper.dev.

Usage

Start the MCP server:

uv run deep_research.py

This will launch the deep_research agent as an MCP server.

Key Components

deep_research.py: Entry point for the MCP server
create_agent.py: Agent creation and configuration
scripts/: Various tools and utilities
- text_web_browser.py: Text-based web browser
- text_inspector_tool.py: File inspection tool
- visual_qa.py: Image analysis tool
- mdconvert.py: Converts various file formats to Markdown

License

This project is provided under the [License Name].

Acknowledgements

This project uses code from HuggingFace's smolagents and Microsoft's autogen projects.