gpt-researcher

Name: gpt-researcher
Availability: InStock
Author: treadwell

Orchestrate autonomous agents to gather sources and generate citation-rich reports.

Updated Feb 5, 2026

Search Tags:#automation #workflow #research #MCP #reporting #citations #retrievers

Ready to run

npx skills add https://github.com/treadwell/gpt-researcher --skill gpt-researcher-treadwell

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: gpt-researcher
Source: https://github.com/treadwell/gpt-researcher/tree/main/.claude
Command: npx skills add https://github.com/treadwell/gpt-researcher --skill gpt-researcher-treadwell

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

GPT Researcher automates complex, cross-domain investigations by orchestrating autonomous agents to gather, organize, and synthesize sources with proper citations. This Skill enables developers and researchers to design configurable, repeatable research workflows without manual intervention.

Core Features & Use Cases

Autonomous agent orchestration for web and local data
Integrated MCP and multiple retrievers to gather diverse sources
Output-rich, citation-backed reports in Markdown, PDF, or DOCX
Use Case: Research a topic like API integration patterns and produce a structured report with references

Quick Start

Instantiate GPTResearcher with a task query, run conduct_research(), then call write_report() to generate the final document. Optionally enable web sockets to stream progress

Frequently Asked Questions about gpt-researcher

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate research workflows to generate citation-rich reports?▼

Automate research workflows by orchestrating autonomous agents to gather, organize, and synthesize web and local data into structured, citation-backed reports. This approach eliminates manual source collection and formatting.

What is autonomous agent orchestration for cross-domain research?▼

Autonomous agent orchestration coordinates agents to investigate topics across domains like software engineering, architecture, and product research. It gathers diverse sources and produces reproducible, citation-rich outputs without manual intervention.

Can I use MCP integration and multiple retrievers for web and local data gathering?▼

Yes, MCP integration and multiple retrievers gather diverse sources from web and local data. This flexible configuration system enables agents to access varied information pools for comprehensive research synthesis.

What's the best way to produce structured reports from automated research?▼

Produce structured reports by running a research query through autonomous agents, then generating the final document in Markdown, PDF, or DOCX. This ensures reproducible workflows with proper citations and references.

Does this autonomous research approach work for software engineering and architecture investigations?▼

Yes, the autonomous research orchestration applies across domains such as software engineering, architecture, and product research. It handles cross-domain investigations by gathering and synthesizing sources with proper citations.

Why use autonomous agents instead of manual research for complex investigations?▼

Autonomous agents automate complex, cross-domain investigations by gathering and organizing sources without manual intervention. This creates configurable, repeatable research workflows that produce citation-backed, structured reports efficiently.