Scholar Relay
# 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.
---
## 🚀 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
---
## 🏗 Tech Stack
- NitroStack MCP
- LangGraph
- TypeScript
- React
- Tailwind CSS
- Node.js
- Zod
- OpenAI API
---
## 🧠 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
---
## 📋 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.
---
## ⚙️ Installation
Clone the repository
```bash
git clone https://github.com/adhithyan05/scholar-relay.git
```
Go to the project folder
```bash
cd scholar-relay
```
Install dependencies
```bash
npm install
```
Run the development server
```bash
npm run dev
```
---
## 🎯 Use Cases
- University Libraries
- Research Institutions
- Students
- Faculty Members
- Literature Reviews
- Thesis and Dissertation Writing
---
## 🌍 Future Enhancements
- Integration with arXiv and Semantic Scholar
- Real-time collaboration
- AI-powered plagiarism prevention
- Personalized research recommendations
- Cloud synchronization
---
## 👥 Team
- Adhithyan S
- Goutham krishna VG
- Devadath Krishna
- Abhinav P Madhu
---
## 📜 License
This project was developed as part of the **NitroStack MCP Hackathon 2026** under the **Education & Research** track.
---
## 🙏 Acknowledgements
- NitroStack
- LangGraph
- OpenAI
- Amrita Vishwa Vidyapeetham
TDQS
Scored across 11 tools
Most tools have clear, distinct purposes, but generate-literature-review appears to encompass discover-papers, summarize-paper, and compare-papers, creating potential overlap. check-citations and readiness-report both relate to citation readiness, though they operate on different inputs (a paragraph vs. a bibliography).
The vast majority of tools follow a verb_noun pattern (e.g., discover-papers, summarize-paper, save-paper). However, readiness-report deviates by using a noun_noun structure, breaking the otherwise consistent convention.
With 11 tools, the server is well-scoped for a research assistant domain. Each tool serves a distinct function in the research workflow, from discovery to citation analysis, without feeling bloated or sparse.
The surface covers the core research lifecycle: search, summarize, compare, generate reviews, find gaps, and manage session state. However, there is no way to remove or update a single saved paper or note, only clear the entire session, which is a notable gap for persistent session management.