Scholar MCP Server is a local academic paper tool offering 9-source search, multi-source PDF downloading, AI-powered analysis, citation graph visualization, and code-based recommendations.

• Search papers (paper_search): Search concurrently across 9 sources (Semantic Scholar, OpenAlex, Crossref, PubMed, arXiv, CORE, Europe PMC, DOAJ, dblp) by keywords or DOI, with relevance scoring, citation impact, and deduplication.

• Download a paper (paper_download): Download a single PDF by DOI via a multi-source fallback chain: Unpaywall → Publisher OA → arXiv → Sci-Hub → scidownl.

• Batch download (paper_batch_download): Download multiple papers at once from a list of DOIs, with per-paper status and summary statistics.

• AI analysis (paper_ai_analyze): Analyze a paper using any OpenAI-compatible API, extracting full text from PDF (up to 20 pages/12k characters) or falling back to the abstract for analysis of contributions, methods, and findings.

• Code-based recommendations (paper_recommend): Scan workspace files (.py, .tex, .md) to detect libraries, algorithms, and LaTeX titles, then auto-recommend related academic papers.

• Citation graph (paper_citation_graph): Generate Mermaid-format citation/reference network visualizations with configurable depth and breadth, plus structured node/edge data.

• Health check (paper_health): Monitor availability of all download sources (Unpaywall, arXiv, Sci-Hub mirrors).

Provides tools to search for and download academic preprints and papers from the arXiv repository.

Enables searching for computer science bibliographical data and author information through the dblp computer science bibliography.

Supports retrieving paper metadata and performing batch downloads of academic papers using Digital Object Identifiers (DOIs).

Facilitates the generation of visual citation and reference networks using Mermaid diagram syntax.

Integrates with various open-access sources and aggregators like DOAJ, CORE, and Unpaywall to find and download freely available research papers.

Enables AI-powered full-text analysis of academic papers using OpenAI-compatible API endpoints for extracting and summarizing information.

Provides tools for searching biomedical literature and life sciences research papers via PubMed and Europe PMC.

Offers broad academic search capabilities and paper data retrieval using the Semantic Scholar database.

1. Click on "Install Server".

2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.

3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Scholar MCP Server Search for recent papers on LLM pruning and summarize the top result"

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.