MCP For Research

🚀 Scholarly Research MCP Server

A consolidated research tool enabling users to find and analyze academic papers from multiple databases with just 5 powerful tools.

🚀 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

1. Download the tool

   git clone https://github.com/aringadre76/mcp-for-research.git
   cd mcp-for-research
   

2. Install dependencies

   npm install
   

3. Build the tool

   npm run build
   

4. Configure 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.js.
   • Set the working directory to your project folder.
5. Test the setup

   npm run test:all-tools-bash
   

✨ 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.

📦 Installation

To install the necessary dependencies, run the following command:

npm install

💻 Usage Examples

Basic Usage

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"
    }
  }
}

📚 Documentation

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 models

Documentation

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 guide

Testing

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 runner

Configuration

├── package.json                       # Project dependencies and scripts
├── tsconfig.json                      # TypeScript configuration
├── .env.example                       # Environment variables template
└── README.md                          # This file

Available Tools

The server provides 5 consolidated MCP tools that replace the previous 24 individual tools:

1. research_search

Comprehensive research paper search across multiple sources with advanced filtering and unified results.

Combines: All individual search tools from PubMed, Google Scholar, ArXiv, and JSTOR. Parameters: Query, sources, filters, display options, sorting.

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.

Combines: Firecrawl integration and web research tools. Parameters: Action, targets, options, crawling limits.

🔧 Technical Details

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.

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-bash

Building

npm run build

Development Mode

npm run dev

📄 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 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.

🤝 Contributing

We welcome contributions! Please see our contributing guidelines and feel free to submit issues or pull requests.

🆘 Support

If you need help:

1. Check the troubleshooting section above.
2. Look at the documentation in the docs/ folder.
3. Open an issue on GitHub.
4. Check the CHANGELOG.md for recent updates.