Scholar Relay

An AI-powered research assistant built using NitroStack MCP and LangGraph that simplifies academic research by helping students discover research papers, generate summaries, build bibliographies, and continue their research seamlessly across multiple devices.

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🚀 Features

• 🔍 Discover relevant research papers based on a topic
• 📄 AI-generated paper summaries
• 📚 Automatic bibliography generation
• 📱 Cross-device session continuation using QR codes
• 📝 Citation verification and unsupported claim detection
• 🎓 Supports multiple citation styles (APA, IEEE, MLA)
• 🤖 Agentic AI workflow powered by LangGraph
• ⚡ Built on NitroStack MCP with Tools, Resources, and Prompts

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🏗 Tech Stack

• NitroStack MCP
• LangGraph
• TypeScript
• React
• Tailwind CSS
• Node.js
• Zod
• OpenAI API

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🧠 MCP Components

Tools

• discover_papers
• summarize_paper
• check_citations
• generate_handoff_token
• notify_readiness_report

Resources

• bibliography://{token}
• catalog://papers
• policy://citation-style

Prompts

• Research Assistant
• Citation Style Formatter
• Report Generator

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📋 Project Workflow

1. Student enters a research topic.
2. AI discovers relevant papers.
3. Papers are summarized.
4. A bibliography is automatically created.
5. The bibliography is stored as an MCP Resource.
6. A QR code is generated for session handoff.
7. Research continues seamlessly on another device.
8. Draft paragraphs are checked for unsupported claims.
9. Missing citations are suggested.
10. A final research readiness report is generated.

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⚙️ Installation

Clone the repository

git clone https://github.com/adhithyan05/scholar-relay.git

Go to the project folder

cd scholar-relay

Install dependencies

npm install

Run the development server

npm run dev

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🎯 Use Cases

• University Libraries
• Research Institutions
• Students
• Faculty Members
• Literature Reviews
• Thesis and Dissertation Writing

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🌍 Future Enhancements

• Integration with arXiv and Semantic Scholar
• Real-time collaboration
• AI-powered plagiarism prevention
• Personalized research recommendations
• Cloud synchronization

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👥 Team

• Adhithyan S
• Goutham krishna VG
• Devadath Krishna
• Abhinav P Madhu

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📜 License

This project was developed as part of the NitroStack MCP Hackathon 2026 under the Education & Research track.

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🙏 Acknowledgements

• NitroStack
• LangGraph
• OpenAI
• Amrita Vishwa Vidyapeetham