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).

Deep Research

Deep Research

Características Principales

Casos de Uso

Características Principales

Casos de Uso