gigaxity-deep-research
FeaturedDeep research MCP server wrapping Qwen3-30B-A3B-Thinking via OpenRouter. Use when an agent needs cross-source synthesis with citations, exploratory expansion of an unfamiliar topic, chain-of-thought reasoning over evidence, or fast conversational lookups grounded in live web search. Exposes six MCP tools — two primitives (search, research) plus four deep-research tools (discover, synthesize, reason, ask) — with matching REST endpoints for each.
Install
Quality Score: 88/100
Skill Content
Details
- Author
- yoloshii
- Repository
- yoloshii/gigaxity-deep-research
- Created
- 4 months ago
- Last Updated
- yesterday
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
deep-research
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
deep-research
Multi-agent research engine that decomposes questions, dispatches parallel searcher agents, synthesizes findings with citations and confidence levels, runs mandatory contrarian/OTB challenges, gap-pursuit verification, and cross-model verification via Gemini CLI, and produces structured output with downstream adapters, research index, and management commands.
deep-research
Multi-agent deep research system for complex questions requiring thorough investigation. Spawns parallel subagents to explore different facets, synthesizes findings into a cited report. Use when the user asks to "research", "deep dive", "investigate", "find out everything about", "comprehensive analysis", "what do we know about", or any question that requires exploring multiple sources and synthesizing findings. Also use when other skills need heavy research (e.g., job-search company research, weekly review trend analysis).