aigroup-paper-mcp
Academic paper search and retrieval MCP server integrating multiple scholarly platforms into a unified interface. Supports search, fetch, trend analysis, and literature review workflows.
README
aigroup-paper-mcp
Academic paper search and retrieval MCP server integrating multiple scholarly platforms into a unified interface.
Overview
aigroup-paper-mcp provides a unified MCP interface for searching, retrieving, and organizing academic paper metadata across major scholarly sources.
It is designed for:
- cross-platform academic paper search
- paper metadata retrieval and browsing
- literature review assistance
- research gap analysis and comparison workflows
- integration with Claude Desktop and other MCP-compatible clients
Highlights
- 12+ academic platforms integrated behind one MCP interface
- 6 advanced tools for search, fetch, discovery, and trend analysis
- 3 resource patterns for direct metadata and category access
- 3 prompt templates for literature-review-style workflows
- structured responses, caching, and parallel search support
Supported Sources
The server currently supports sources such as:
- arXiv
- OpenAlex
- PubMed Central (PMC)
- Europe PMC
- bioRxiv
- medRxiv
- CORE
- Semantic Scholar
- Crossref
- PubMed
- Google Scholar
- IACR
Quick Start
Requirements
- Node.js >= 18
- npm
Install and build locally
git clone https://github.com/jackdark425/aigroup-paper-mcp.git
cd aigroup-paper-mcp
npm install
npm run build
npm start
Run as CLI with npx
npx aigroup-paper-mcp --help
npx aigroup-paper-mcp search "machine learning"
npx aigroup-paper-mcp fetch "2301.00001" --source arxiv
MCP Client Configuration
Claude Desktop / RooCode / compatible MCP clients
{
"mcpServers": {
"aigroup-paper-mcp": {
"command": "npx",
"args": ["aigroup-paper-mcp"]
}
}
}
Tools
search_papers
Cross-platform paper search with smart source selection and query optimization.
fetch_paper
Fetches detailed metadata for a paper by source and identifier.
fetch_latest
Gets the latest papers from a selected source/category.
list_categories
Lists supported categories for a given platform.
advanced_search
Supports more complex boolean-style academic search queries.
trend_analysis
Analyzes topic evolution and publication trends over time.
Resources
paper://{source}/{id}category://{source}/{category}search://{query}
Prompt Templates
literature_reviewresearch_gap_analysispaper_comparison
Environment Variables
Create a .env file if needed:
LOG_LEVEL=info
CACHE_ENABLED=true
CACHE_TTL=3600
MAX_SEARCH_LIMIT=100
Project Structure
aigroup-paper-mcp/
├── src/
├── docs/
├── scripts/
├── package.json
└── README.md
Development
npm run build
npm run test
npm run lint
License & Usage
This project is released under the MIT License.
You may use, copy, modify, merge, publish, distribute, sublicense, and sell copies of this software, including in academic, internal, and commercial contexts, provided that the original copyright notice and license text are preserved.
Please keep in mind:
- the software is provided "AS IS", without warranty of any kind
- you must retain the relevant copyright and permission notice in copies or substantial portions of the software
- downstream usage remains subject to the terms, rate limits, metadata rules, and access restrictions of upstream academic data providers
See the full text in LICENSE.
Acknowledgments
Scholarly Data Ecosystem
Thanks to the academic and open metadata ecosystems that make federated retrieval possible, including arXiv, OpenAlex, PubMed, Crossref, Semantic Scholar, and related services.
MCP Ecosystem
- Model Context Protocol SDK
- Repository: https://github.com/modelcontextprotocol/servers
- Role: MCP server integration and tool/resource/prompt model
Support
- Issues: https://github.com/jackdark425/aigroup-paper-mcp/issues
- Repository: https://github.com/jackdark425/aigroup-paper-mcp
- Docs: https://github.com/jackdark425/aigroup-paper-mcp/tree/main/docs
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