# Paper Search MCP Server

> Search and download academic papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, Semantic Scholar, and IACR. Fetch PDFs and extract full text to accele

- Price: Free to connect · provider's own fees apply
- URL: https://daas.listeningmind.ai/en/catalog/mcps/x-mcp-adamamer20-paper-search-mcp-openai
- Source: Smithery https://smithery.ai/server/adamamer20/paper-search-mcp-openai
- Rank this week: #3 (score 80)

## Install

```
npx -y @smithery/cli install adamamer20/paper-search-mcp-openai --client claude
```
- Remote: https://paper-search-mcp-openai--adamamer20.run.tools

## Tools (25)

- `search`: Deep Research compatible search tool aggregating across sources.
- `fetch`: Fetch full document content for a search result.
- `search_arxiv`: Search academic papers from arXiv. Args: query: Search query string (e.g., 'machine learning'). maxresults: Maximum number of papers to return (default: 10).
- `search_pubmed`: Search academic papers from PubMed. Args: query: Search query string (e.g., 'machine learning'). maxresults: Maximum number of papers to return (default: 10).
- `search_biorxiv`: Search academic papers from bioRxiv. Args: query: Search query string (e.g., 'machine learning'). maxresults: Maximum number of papers to return (default: 10).
- `search_medrxiv`: Search academic papers from medRxiv. Args: query: Search query string (e.g., 'machine learning'). maxresults: Maximum number of papers to return (default: 10).
- `search_google_scholar`: Search academic papers from Google Scholar. Args: query: Search query string (e.g., 'machine learning'). maxresults: Maximum number of papers to return (default: 10).
- `search_iacr`: Search academic papers from IACR ePrint Archive. Args: query: Search query string (e.g., 'cryptography', 'secret sharing').
- `download_arxiv`: Download PDF of an arXiv paper. Args: paperid: arXiv paper ID (e.g., '2106.12345'). savepath: Directory to save the PDF (default: './downloads').
- `download_pubmed`: Attempt to download PDF of a PubMed paper. Args: paperid: PubMed ID (PMID). savepath: Directory to save the PDF (default: './downloads').
- `download_biorxiv`: Download PDF of a bioRxiv paper. Args: paperid: bioRxiv DOI. savepath: Directory to save the PDF (default: './downloads'). Returns: Path to the downloaded PDF file.
- `download_medrxiv`: Download PDF of a medRxiv paper. Args: paperid: medRxiv DOI. savepath: Directory to save the PDF (default: './downloads'). Returns: Path to the downloaded PDF file.
- `download_iacr`: Download PDF of an IACR ePrint paper. Args: paperid: IACR paper ID (e.g., '2009/101'). savepath: Directory to save the PDF (default: './downloads').
- `read_arxiv_paper`: Read and extract text content from an arXiv paper PDF. Args: paperid: arXiv paper ID (e.g., '2106.12345').
- `read_pubmed_paper`: Read and extract text content from a PubMed paper. Args: paperid: PubMed ID (PMID). savepath: Directory where the PDF would be saved (unused).
- `read_biorxiv_paper`: Read and extract text content from a bioRxiv paper PDF. Args: paperid: bioRxiv DOI. savepath: Directory where the PDF is/will be saved (default: './downloads').
- `read_medrxiv_paper`: Read and extract text content from a medRxiv paper PDF. Args: paperid: medRxiv DOI. savepath: Directory where the PDF is/will be saved (default: './downloads').
- `read_iacr_paper`: Read and extract text content from an IACR ePrint paper PDF. Args: paperid: IACR paper ID (e.g., '2009/101').
- `search_semantic`: Search academic papers from Semantic Scholar. Args: query: Search query string (e.g., 'machine learning').
- `download_semantic`: Download PDF of a Semantic Scholar paper. Args: paperid: Semantic Scholar paper ID, Paper identifier in one of the following formats: - Semantic Scholar ID (e.g., "649def34f8be52c8…
- `read_semantic_paper`: Read and extract text content from a Semantic Scholar paper. Args: paperid: Semantic Scholar paper ID, Paper identifier in one of the following formats: - Semantic Scholar ID (e.g.…
- `search_crossref`: Search academic papers from CrossRef database. CrossRef is a scholarly infrastructure organization that provides persistent identifiers (DOIs) for scholarly content and metadata.
- `get_crossref_paper_by_doi`: Get a specific paper from CrossRef by its DOI. Args: doi: Digital Object Identifier (e.g., '10.1038/nature12373').
- `download_crossref`: Attempt to download PDF of a CrossRef paper. Args: paperid: CrossRef DOI (e.g., '10.1038/nature12373'). savepath: Directory to save the PDF (default: './downloads').
- `read_crossref_paper`: Attempt to read and extract text content from a CrossRef paper. Args: paperid: CrossRef DOI (e.g., '10.1038/nature12373').

## FAQ

### What is the Paper Search MCP Server?

Search and download academic papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, Semantic Scholar, and IACR. Fetch PDFs and extract full text to accele. It is listed on Smithery and ranks #3 (score 80) in ListeningMind.AI's weekly picks.

### How do I install the Paper Search MCP Server?

Run npx -y @smithery/cli install adamamer20/paper-search-mcp-openai --client claude in a terminal to add it to Claude Desktop. For Cursor, use --client cursor.

### Do I need an API key?

The provider lists no required settings.

### Which tools does it provide?

25 tools: search, fetch, search_arxiv, search_pubmed, search_biorxiv, search_medrxiv, search_google_scholar, search_iacr, download_arxiv, download_pubmed, download_biorxiv, download_medrxiv.

### How much does it cost?

Free to connect · provider's own fees apply. The provider may charge for use on its own terms.

### Can I trust it?

Checks passed: In the official MCP Registry, Own homepage, Live endpoint, Clear description. Skim a server or repository you have not used before connecting it.