Enables searching and retrieving academic papers from arXiv, providing access to preprints in physics, mathematics, computer science, and other scientific disciplines.
Provides web scraping capabilities to search Google Scholar for academic papers, citations, and scholarly literature across multiple disciplines.
Integrates with PubMed's API to search and retrieve biomedical and life sciences literature, including full paper analysis and citation management.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Scholarly Research MCP Serverfind recent papers on quantum computing algorithms"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Scholarly Research MCP Server
A powerful, consolidated research tool that helps you find and analyze academic research papers from PubMed, Google Scholar, ArXiv, and JSTOR through just 5 powerful tools.
What This Tool Does
This tool helps you:
Find research papers on any topic from multiple academic databases
Read full papers when available (not just abstracts)
Extract key information like quotes, statistics, and findings
Get citations in the format you need for your work
Search within papers to find specific information
Organize research with customizable preferences
Related MCP server: Academic Paper Search MCP Server
Key Features
5 Consolidated Tools: Powerful, multi-functional tools instead of 24 separate ones
Multi-Source Search: PubMed, Google Scholar, ArXiv, and JSTOR
User Preferences: Customizable search and display settings
Content Extraction: Full-text paper access and analysis
Citation Management: Multiple citation format support
Error Handling: Robust fallback mechanisms
Web research (Firecrawl): When
FIRECRAWL_API_KEYis set in the environment (or a Firecrawl client is provided), theweb_researchtool can scrape URLs and run web search. See Configuration and copy.env.exampleto.envto set your key. Get an API key at firecrawl.dev.
Configuration
Do not hardcode API keys. Set all keys via environment variables only (e.g. copy .env.example to .env and fill in values there). Never commit .env (it is in .gitignore).
Optional environment variables:
FIRECRAWL_API_KEY: Enables the
web_researchtool (scrape, search) and optional Firecrawl-based Google Scholar inresearch_searchwhen the preference is set. Leave unset if you do not use Firecrawl.PUBMED_API_KEY: Optional. NCBI/E-utilities API key for higher rate limits. Leave unset to use PubMed without a key.
Project Structure
This tool is organized into several key components:
Core Components
src/
├── index.ts # Main server entry point (consolidated)
├── adapters/ # Data source connectors
│ ├── pubmed.ts # PubMed API integration
│ ├── google-scholar.ts # Google Scholar web scraping
│ ├── google-scholar-firecrawl.ts # Firecrawl integration
│ ├── arxiv.ts # ArXiv integration
│ ├── unified-search.ts # Basic multi-source search
│ ├── enhanced-unified-search.ts # Advanced multi-source search
│ └── preference-aware-unified-search.ts # User preference integration
├── preferences/ # User preference management
│ └── user-preferences.ts # Preference storage and retrieval
└── models/ # Data structures and interfaces
├── paper.ts # Paper data models
├── search.ts # Search parameter models
└── preferences.ts # Preference modelsDocumentation
docs/
├── README.md # Documentation index and overview
├── CONSOLIDATION_GUIDE.md # Complete consolidation guide
├── TOOL_CONSOLIDATION.md # Quick tool mapping reference
├── PROJECT_STRUCTURE.md # Clean project organization
├── API_REFERENCE.md # Complete API documentation
├── ARCHITECTURE.md # Technical system design
├── DATA_MODELS.md # Data structure definitions
├── DEVELOPMENT.md # Developer setup guide
└── TROUBLESHOOTING.md # Problem-solving guideTesting
tests/
├── test-preferences.js # Preference system tests
├── test-all-tools-simple.sh # Bash test runner (recommended)
├── test_all_tools.py # Python test runner
└── test-all-tools.js # JavaScript test runnerConfiguration
├── package.json # Project dependencies and scripts
├── tsconfig.json # TypeScript configuration
├── .env.example # Environment variables template
└── README.md # This fileAvailable Tools
The server provides 5 consolidated MCP tools that replace the previous 24 individual tools:
1. research_search
Comprehensive research paper search across PubMed, Google Scholar, and ArXiv. Uses the preference-aware adapter: when Firecrawl is configured and the preference is set, Google Scholar can use Firecrawl instead of Puppeteer. JSTOR is accepted in sources but not implemented; if requested, a note is appended: "JSTOR is not implemented; results are from other sources."
Parameters: Query, sources (pubmed, google-scholar, arxiv, jstor), maxResults, startDate, endDate, journal, author, includeAbstracts, sortBy
2. paper_analysis
Get comprehensive paper information, full text, and analysis including quotes, statistics, and findings.
Combines: Paper retrieval, content extraction, and analysis tools Parameters: Identifier, analysis type, quote limits, section lengths
3. citation_manager
Generate citations in multiple formats and get citation information including counts and related papers.
Combines: Citation tools, citation counting, and related paper discovery Parameters: Identifier, action, format, related paper limits
4. research_preferences
Manage research preferences including source priorities, search settings, display options, and caching.
Combines: All preference management tools Parameters: Action, category, various preference values
5. web_research
Perform web-based research using Firecrawl for reliable content extraction and analysis.
Requires: Set FIRECRAWL_API_KEY for scrape and search. Extract, map, and crawl are not implemented; use scrape or search.
Parameters: Action (scrape, search, extract, map, crawl), url, query, maxResults, formats, onlyMainContent, waitFor
Quick Start
Option 1: Use Through AI Assistants (Easiest - No Setup Required)
If you're not comfortable with technical setup, you can use this tool through AI assistants like:
Claude (Anthropic)
ChatGPT (OpenAI)
Cursor (Code editor with AI)
These assistants can use this tool to help you find research papers without any setup on your part.
Option 2: Set Up MCP on Your Computer (For Advanced Users)
This option lets you use the tool directly with AI assistants on your computer. It's like giving your AI assistant a special tool to find research papers.
Setting Up MCP (Model Context Protocol)
MCP is like a "language" that lets AI assistants talk to tools on your computer. Think of it like installing a special app that your AI assistant can use.
What You Need
A computer (Windows, Mac, or Linux)
An AI assistant that supports MCP (like Claude Desktop, Cursor, or others)
Basic computer skills (downloading files, running programs)
Step-by-Step Setup
Download the tool
git clone https://github.com/aringadre76/mcp-for-research.git cd mcp-for-researchInstall dependencies
npm installBuild the tool
npm run buildConfigure your AI assistant
Find "MCP Servers" or "Tools" in your AI assistant's settings
Add a new MCP server
Set the command to:
node dist/index.jsSet the working directory to your project folder
Test the setup
npm run test:all-tools-bash
Usage Examples
Search for Papers
{
"method": "tools/call",
"params": {
"name": "research_search",
"arguments": {
"query": "machine learning",
"sources": ["pubmed", "arxiv"],
"maxResults": 15,
"startDate": "2020/01/01"
}
}
}Analyze a Paper
{
"method": "tools/call",
"params": {
"name": "paper_analysis",
"arguments": {
"identifier": "12345678",
"analysisType": "complete",
"maxQuotes": 20
}
}
}Get Citations
{
"method": "tools/call",
"params": {
"name": "citation_manager",
"arguments": {
"identifier": "12345678",
"action": "all",
"format": "apa"
}
}
}Benefits of the Consolidated Approach
✅ 80% reduction in tool count (24 → 5)
✅ Easier to remember and use
✅ More powerful - multiple operations in single calls
✅ Better performance - fewer tool registrations
✅ Easier maintenance - less code duplication
✅ Consistent interface - similar parameter patterns
Migration from Previous Version
The consolidated tools are backward compatible - you can still access the same functionality, just through fewer, more powerful tools. Each consolidated tool accepts parameters that let you specify exactly what you want to do.
Old Tool | New Tool | Notes |
|
| Use |
|
| Use |
|
| Use |
|
| Use |
|
| Use |
Troubleshooting
Common Issues
Q: The tool doesn't start
A: Make sure you've run npm install and npm run build first.
Q: My AI assistant can't find the tools A: Check that the MCP server path is correct in your AI assistant's settings.
Q: Searches return no results A: Try different search terms or check if your sources are enabled in preferences.
Q: How do I get papers in a specific format? A: Use the citation tools to get the paper in the format you need (APA, MLA, etc.).
Development
Running Tests
npm run test:all-tools-bashBuilding
npm run buildDevelopment Mode
npm run devContributing
We welcome contributions! Please see our contributing guidelines and feel free to submit issues or pull requests.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Documentation
For comprehensive documentation, guides, and technical details, see the docs/ directory:
Documentation Overview - Complete documentation index
Consolidation Guide - Detailed explanation of the new approach
Tool Reference - Quick mapping from old to new tools
API Reference - Complete tool documentation
Project Structure - Clean project organization
Support
If you need help:
Check the troubleshooting section above
Look at the documentation in the
docs/folderOpen an issue on GitHub
Check the CHANGELOG.md for recent updates
Version History
v2.0.0: Consolidated 24 tools into 5 powerful tools
v1.4.x: Previous version with 24 individual tools
v1.0.x: Initial release
Note: This tool is designed to be easy to use while providing powerful research capabilities. The consolidated approach makes it simpler to use while maintaining all the functionality of the previous version. the previous version. s version. the previous version.
Appeared in Searches
- A server for searching academic papers and retrieving metadata
- Resources and information about studying
- General research information and resources
- A search for literature reviews and academic research resources
- A server for searching research papers, Kaggle datasets, and websites for ML/AI model training data