MCP Research Assistant Server AI-powered research assistant with web search, academic search, and document Q&A capabilities. Can operate as an MCP server for AI clients or in direct query mode. ## Features - Web Search: Search the web via GDELT news and content APIs - Academic Search: Search research papers via OpenAlex - News Search: Real-time news monitoring - Data Extraction: Extract structured data from web pages - AI Summarization: Multi-LLM support for research synthesis - MCP Server Mode: Expose as Model Context Protocol server ## Data Sources (All Free) | Source | Data Type | |--------|-----------| | GDELT | Web content, news articles | | OpenAlex | Academic papers, citations | | Wikipedia | Encyclopedia articles | | arXiv | Preprints (physics, CS, math) | | Semantic Scholar | Research papers | | CrossRef | DOI metadata | ## Operating Modes ### Direct Query Mode Run standalone research queries with AI synthesis. ### MCP Server Mode Expose tools for AI clients (Claude, GPT) to call: - web_search: Search web content - academic_search: Search research papers - news_search: Search news articles - summarize: Summarize content with AI ## Input Parameters | Parameter | Type | Description | |-----------|------|-------------| | mode | string | "query" (direct) or "server" (MCP) | | query | string | Research question (for direct mode) | | tools | array | Tools: web_search, news_search, academic_search, data_extraction, summarization | | modelName | string | AI model for synthesis | ## Output json { "success": true, "query": "What are the latest developments in AI agents?", "research_report": { "summary": "AI agents have seen rapid development in 2024...", "key_findings": [ "Multi-agent systems showing promise", "Tool use capabilities expanding", "Memory and planning improvements" ], "sources": [ { "title": "Survey of AI Agent Architectures", "source": "arXiv", "url": "https://arxiv.org/abs/...", "date": "2024-01-10", "relevance": 0.95 } ], "academic_papers": [ { "title": "ReAct: Synergizing Reasoning and Acting", "authors": ["Yao et al."], "venue": "ICLR 2023", "citations": 500, "link": "https://..." } ], "news_coverage": [...], "ai_synthesis": { "main_themes": [...], "research_gaps": [...], "future_directions": [...] } } } ## Use Cases 1. Researchers: Literature review, research synthesis 2. Analysts: Market research, competitive analysis 3. Students: Academic research assistance 4. Journalists: Background research, fact-checking 5. AI Developers: MCP server integration ## Pricing Pay-per-event model: - search-performed: $0.01 per search - document-processed: $0.005 per document - ai-synthesis: $0.02 per synthesis ## Example Usage ### Direct Query Mode bash apify call fiery_dream/mcp-research-server --input '{ "mode": "query", "query": "What are the latest developments in quantum computing?", "tools": ["web_search", "academic_search", "summarization"], "modelName": "gpt-4o-mini", "openaiApiKey": "sk-..." }' ### MCP Server Mode bash apify call fiery_dream/mcp-research-server --input '{ "mode": "server" }'