All 207 Dependencies
Every package GPT Researcher depends on, ranked by repo health score.
GPT Researcher is the first open-source autonomous research agent purpose-built to overcome the core weaknesses of LLM-based research: hallucination, token limits, shallow sourcing, and selective bias. Rather than querying a single source, it dispatches parallelized planner and executor agents that query 20+ web sources, scrape JavaScript-rendered pages, ingest local documents, and aggregate findings through RAG and Plan-and-Solve pipelines into a single, coherent, citation-backed report.
The system ships as both a Python pip package for programmatic integration and a full-stack application with a FastAPI backend, WebSocket-driven real-time streaming, and two frontend options: a lightweight HTML/CSS/JS interface and a production-ready Next.js frontend. Reports can be exported as PDF, Word, Markdown, JSON, or CSV, making it adaptable to journalistic, academic, enterprise, and developer workflows.
Version 3.x introduced Deep Research, a recursive tree-exploration mode that fans out into subtopics with configurable depth and breadth, spending roughly five minutes and $0.40 per investigation to produce genuinely comprehensive coverage. Alongside it, MCP (Model Context Protocol) integration enables research against GitHub repositories, databases, and custom APIs alongside conventional web search, and inline AI image generation via Google Gemini embeds contextually appropriate illustrations directly in the output report.
With over 27,000 GitHub stars, 70+ releases, and 200+ contributors, GPT Researcher has become the de facto reference implementation for autonomous research agents, used as both a standalone tool and as a research backend embedded in multi-agent systems built with LangGraph, AG2, and Claude.