{"id":"gpt-researcher","name":"GPT Researcher","homepage":"https://gptr.dev","repo_url":"https://github.com/assafelovic/gpt-researcher","category":"ai-ml","subcategories":["research","report-generation","web-scraping"],"tags":["deep-research","autonomous-agent","multi-source","citations","langchain","langgraph","tavily","python"],"what_it_does":"Autonomous research agent that plans research questions, scrapes and validates multiple web and local sources, then synthesizes findings into detailed cited reports exceeding 2000 words with 20+ sources.","use_cases":["Market research and competitive analysis with cited sources","Academic literature review and synthesis across multiple papers","Investment due diligence and company analysis","Technical documentation research and fact-checking","News trend analysis aggregating multiple perspectives"],"not_for":["Real-time or sub-second search results","Simple single-query lookups where a search engine suffices","Offline-only environments with no web access","Tasks requiring deterministic, reproducible outputs"],"best_when":"You need thorough, multi-source research synthesized into a cohesive report with citations, and can tolerate ~30-second to 5-minute processing times and per-query LLM costs.","avoid_when":"You need instant answers, have no budget for LLM API costs, or need fully reproducible deterministic outputs.","alternatives":[{"name":"Tavily","note":"Simpler web search API without autonomous agent orchestration"},{"name":"Perplexity","note":"Hosted research assistant with faster responses but less depth"},{"name":"AutoGPT","note":"General autonomous agent, not research-specialized"}],"af_score":45.8,"security_score":0.0,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"unknown","last_evaluated":"2026-03-01T09:50:05.649229+00:00","performance":{"latency_p50_ms":30000,"latency_p99_ms":300000,"uptime_sla_percent":null,"rate_limits":"Dependent on upstream API rate limits (OpenAI, Tavily)","data_source":"llm_estimated","measured_on":null}}