Deep Research FAQs

Question 1

How does Deep Research work?

Accepted Answer

Deep Research utilizes a modular design where various AI agents (e.g., ResearchAgent, EditorAgent) communicate through MCP. It stores data in typed dictionaries and uses a FastMCP server as the entry point for task execution. Users can customize the agents and their interactions to fit specific research needs.

Question 2

What is Deep Research?

Accepted Answer

Deep Research is a Python-based framework that orchestrates AI agents to automate research tasks. It uses a multi-agent system managed through FastMCP (Message Control Protocol) to handle tasks such as information retrieval, analysis, and report generation.

Question 3

What are the setup requirements for Deep Research?

Accepted Answer

To set up Deep Research, you need to clone the repository, configure your `.env` file with necessary API keys, install dependencies using `pip`, configure your `claude_desktop_config.json` file, and run the `mcp_server.py` script.

Question 4

Can I customize the AI agents within Deep Research?

Accepted Answer

Yes, Deep Research is designed with a modular architecture, allowing you to customize the existing AI agents or create new ones tailored to your specific research requirements.

Question 5

What are the key features of Deep Research?

Accepted Answer

Key features include multi-agent orchestration, integration with FastMCP servers, modular and customizable AI agents, typed dictionaries for managing research data, and communication via Message Control Protocol (MCP).

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