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

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_KEY is set in the environment (or a Firecrawl client is provided), the web_research tool can scrape URLs and run web search. See Configuration and copy .env.example to .env to set your key. Get an API key at firecrawl.dev.

Configuration Overview

Configuration for environment variables and API keys is documented in more detail in the docs/ folder and .env.example. At a high level, you configure API keys via environment variables and should avoid committing any secret values.

Project Structure

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

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

Quick Start

Pick your AI tool below to get started quickly:

Cursor is a true one-click install via the deeplink above. For other tools, the buttons jump to the relevant configuration section.

Claude Desktop – Copy configuration

Add this to your claude_desktop_config.json under mcpServers:

{
  "mcpServers": {
    "scholarly-research-mcp": {
      "command": "npx",
      "args": ["-y", "scholarly-research-mcp"]
    }
  }
}

Then fully restart Claude Desktop.
Config file locations:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%/Claude/claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

Cursor IDE – One‑click install

If you use Cursor, you can install this MCP server with a single click:

One‑Click – Add to Cursor

This opens Cursor and pre-fills an MCP server that runs npx -y scholarly-research-mcp. You’ll need Node.js and npm available on your system.

VS Code – Copy configuration

Create .vscode/mcp.json in your project (or edit your global MCP config) and add:

{
  "servers": {
    "scholarly-research-mcp": {
      "command": "npx",
      "args": ["-y", "scholarly-research-mcp"]
    }
  }
}

Then reload VS Code so the Copilot / MCP integration picks it up.

Claude Code / Gemini / Codex – CLI

If your tool lets you point at a local MCP server command, use:

npx -y scholarly-research-mcp

or, after cloning this repo and building:

node dist/index.js

Configure your AI tool to use that command as an MCP server.

Manual – Copy configuration JSON

For any MCP-compatible assistant that accepts a JSON config (similar to mcp.json), use:

{
  "mcpServers": {
    "scholarly-research-mcp": {
      "command": "npx",
      "args": ["-y", "scholarly-research-mcp"]
    }
  }
}

Paste this into the assistant’s MCP configuration and adjust paths/env vars if needed.

Requirements

• Node.js >= 18.17 (LTS recommended). Check with node -v.
• npm (comes with Node.js).
• Google Chrome or Chromium (optional) – only needed for Google Scholar scraping and ArXiv full-text extraction. If you only use PubMed, ArXiv API search, or Firecrawl-based features, no browser is required. You can point to a custom binary with PUPPETEER_EXECUTABLE_PATH or CHROME_PATH.

Local MCP 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
   

6. Connect from your AI assistant

   • Open your assistant's settings and find the section for MCP servers or tools.
   • Add a new MCP server that runs the command node dist/index.js in the mcp-for-research folder.
   • Save the configuration and ask the assistant to list or use the research_search tool to confirm it is working.

Available 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 ca

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