mcpField
M
mcp-scholaris

mcp-scholaris

Local
github.com/penny4nonsenseSearch0Updated 18w ago
Repository

About mcp-scholaris

mcp-scholaris is an MCP server for searching academic papers and retrieving available open-access full text. It serves researchers and readers with coverage across arXiv, Semantic Scholar, and PubMed, plus Unpaywall lookup for open versions.

Key features

  1. 01Search by topic, author, or keyword
  2. 02Search across arXiv, Semantic Scholar, and PubMed
  3. 03Retrieve arXiv PDF full text
  4. 04Fetch PubMed Central articles via BioC
  5. 05Find open-access versions through Unpaywall

Use cases

  1. 01Find papers on a research topic
  2. 02Retrieve an available open-access paper
  3. 03Locate an open version of a DOI article

MCP support

It exposes paper search and retrieval tools to MCP clients over stdio using JSON-RPC 2.0.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "penny4nonsense-mcp-scholaris": {
      "command": "uvx",
      "args": [
        "mcp-scholaris"
      ]
    }
  }
}
Run commanduvx mcp-scholaris

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypimcp-scholaris0.1.3

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

mcp-scholaris

An MCP server for retrieving academic papers from open access sources. Provides search across arXiv, Semantic Scholar, and PubMed, with full text retrieval via arXiv PDFs, PubMed Central (BioC API), and Unpaywall. No paywalls, no grey area — legitimate open access only.

Installation

pip install mcp-scholaris

Tools

search_papers

Search for academic papers by topic, author, or keyword.

Parameters:

  • query (required) — search terms
  • sources (optional) — list of sources to search: arxiv, semantic_scholar, pubmed. Defaults to all three.
  • max_results (optional) — maximum results per source. Defaults to 5.
fetch_paper

Fetch the full text of a paper. Tries open access sources in order: arXiv → PubMed Central → Unpaywall. Provide at least one identifier.

Parameters:

  • arxiv_id — e.g. 2301.00001 or arxiv:2301.00001
  • pubmed_id — PubMed ID (PMID), e.g. 36383508
  • doi — e.g. 10.1371/journal.pone.0276755

Configuration

Semantic Scholar works without an API key but is rate-limited. For higher limits, create a .env file in your working directory:

SEMANTIC_SCHOLAR_API_KEY=your_key_here

API keys are free at semanticscholar.org.

Usage with an MCP client

Add to your MCP client configuration:

{
  "mcpServers": {
    "scholaris": {
      "command": "scholaris"
    }
  }
}

Or run directly:

scholaris

The server communicates over stdio using the MCP protocol (JSON-RPC 2.0).

Sources

SourceSearchFull Text
arXiv✓✓ PDF
Semantic Scholar✓✓ when OA PDF available
PubMed✓✓ via BioC API (PMC articles)
Unpaywall—✓ for any DOI with OA version

License

MIT

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.