Scholar

Scholar MCP Server

A Model Context Protocol (MCP) server providing structured access to scientific literature databases. It serves as a unified interface for Scopus, OpenAlex, Semantic Scholar, and Unpaywall, enabling AI agents to perform systematic paper discovery, author disambiguation, citation lineage tracking, and multimodal Content extraction.

Core Capabilities

• Unified Literature Search
• Semantic Scholar Integration — High-relevance search and detailed metadata, including AI-generated TLDRs (requires API key).
• Scopus Integration — Targeted metadata retrieval via advanced Boolean syntax (requires API key).
• OpenAlex Integration — Broad search across 250M+ works with abstract reconstruction.
• Unpaywall Resolution — DOI-to-PDF cross-referencing across global Open Access repositories.
• Sci-Hub Fallback (⚠️ Use with Caution) — Automatic mirror resolution and parsing for paywall bypassing.

• Book Search & Extraction
• Google Books & Open Library — Integrated search for book metadata, editions, and descriptions without API keys.
• Library Genesis (Libgen) — Search and extract full text from books directly using PyMuPDF. Features smart caching and token-saving strategies (TOC reading, targeted keyword searching, and page range extraction).

• Author Identification & Metrics
• Instant author disambiguation and ID resolution via OpenAlex autocomplete.
• Comprehensive profiles: H-index, i10-index, institutional affiliation history, and ORCID linkage.
• Precision metrics from Elsevier (Scopus) for verified publication counts.

• Citation Lineage Tracking
• Map research evolution through forward citations (citing works) and backward references (cited works).

• Structured & Multimodal Extraction
• Text Extraction — Layout-aware parsing of OA PDFs using PyMuPDF.
• Vision Rendering — Page-by-page PNG rendering for LLM-based analysis of charts, tables, and equations.
• HTML Fallbacks — Extraction from web-based research resources via BeautifulSoup.

• Topic Mapping & Field Analysis
• Concepts and domain hierarchy discovery to map research landscapes.
• Batch metadata retrieval for high-throughput literature processing (up to 50 DOIs/request).

• Access Management & Fallbacks
• Automated detection of closed-access content with human-in-the-loop instructions for manual uploads.

Architecture

graph TD

A[LLM Agent] -->|MCP Protocol| B(Scholar MCP Server) B --> C{Database Router} C -->|Primary| D[Scopus API] C -->|Fallback| E[OpenAlex API] C -->|DOI Resolver| F[Unpaywall API] C -->|Citations| P[CrossRef API]

D --> G{Access Check} E --> G F --> G P --> G

G -->|Open Access| H[PDF Buffer Download] G -->|Closed Access| I[Human-in-the-Loop Prompt] H --> J[PyMuPDF Text Extractor] H --> K[PyMuPDF Vision Renderer] J --> L[Return Context to LLM] K --> L I --> L B --> M{Author Router} M -->|Profile| N[OpenAlex Authors API] M -->|Metrics| O[Scopus Author API] N --> L O --> L

Installation

Quick Start (via PyPI)

The fastest way to use the server is directly via PyPI:

pip install scholar-academic-mcp

Manual Setup (for Development)

# Clone the repository

git clone https://github.com/mlintangmz2765/Scholar-MCP.git cd Scholar-MCP

Setup virtual environment

python -m venv venv .\venv\Scripts\activate # Windows source venv/bin/activate # Unix

Install in editable mode

pip install -e .

Environment Variables

Configuration

Claude Desktop / Cursor

Add the following to your configuration file (e.g., claude_desktop_config.json):

{

"mcpServers": { "scholar-academic-mcp": { "command": "scholar-academic-mcp", "env": { "SCOPUS_API_KEY": "your_scopus_api_key", "S2_API_KEY": "your_s2_api_key", "SCIHUB_MIRRORS": "https://sci-hub.ru,https://sci-hub.st", "LIBGEN_MIRRORS": "https://libgen.la,http://libgen.li", "SCOPUS_INST_TOKEN": "your_optional_inst_token", "CONTACT_EMAIL": "your_email@domain.com" } } } }

Quick Start & Examples

Once configured, your AI agent can perform complex research workflows. Below are representative examples of tool inputs and structured outputs.

1. Literature Discovery (Scopus)

Prompt: *"Find recent papers about 'Transformer architectures' published after 2022 using Scopus."*

Tool Call: search_papers_tool(query="TITLE-ABS-KEY(Transformer architectures) AND PUBYEAR > 2022", limit=3)

Output:

Found 3 papers via Scopus:

• [SCOPUS_ID:85184...] Attention is All You Need? A Survey of Transformer Variants Authors: Smith, J., Doe, A. Date: 2024-01-15 | DOI: 10.1016/j.artint.2023.104012

2. Multimodal Content Analysis

Prompt: *"I need to see the diagram for the neural network architecture on page 3 of this URL."*

Tool Call: get_full_text_visual_tool(url="https://arxiv.org/pdf/1706.03762.pdf", max_pages=3)

Output:

• [Text] "Successfully rendered 3 pages visually..."
• [Image] (PNG data of page 1)
• [Image] (PNG data of page 2)
• [Image] (PNG data of page 3 - containing the architecture diagram)

3. Research Topic Mapping

Prompt: *"Help me understand the subfields and domains related to 'Generative AI'."*

Tool Call: search_topics_tool(query="Generative AI")

Output:

Found 1 topics for 'Generative AI':

• Artificial Intelligence Hierarchy: Computer Science → Artificial Intelligence → Machine Learning Works: 12,450 | Citations: 450,210 Description: A field of computer science that focuses on creating systems capable of generating...

Tools

The server registers 23 tools across 7 categories:

Paper Discovery

Book Discovery & Extraction

Author Analytics

Citation Tracking

| get_citations_tool| `(paper_id, direction="references"