gpt-researcher

Automated research orchestration coordinates planning, data gathering, and report writing across web and local sources to produce structured, cited Markdown reports. You initialize with a query, invoke conduct_research(), and call write_report() for findings.

Building domain-specific research agents requires modular orchestration supporting custom retrievers, skills, and prompts. This tailors research workflows for specific tasks by automating sub-query processing and multi-source investigations with traceable outputs.

Yes, you can integrate MCP data and local retrievers into automated research workflows. The modular orchestration supports adding new retrievers and MCP integration to coordinate data gathering across web and local sources for comprehensive reporting.

WebSocket-based progress streaming provides live updates during automated research orchestration. It monitors modular components like agent selection, planning, sub-query processing, and report writing, enabling real-time tracking during multi-source investigations.

Yes, automated report generation supports optional image generation. The modular orchestration integrates image generation alongside planning, data gathering, and report writing to enrich structured, cited outputs for domain-specific research agents.

Modular orchestration automates end-to-end web and local research tasks to produce structured, cited reports, reducing manual workload. It coordinates sub-query processing and agent selection, increasing clarity and traceability for complex literature surveys.