Log inSubmit server
Scholar logo

Scholar

Research literature, authors, citations, books, open-access PDFs, and document visuals through MCP tools.

InstallRepositoryWebsite
Full README Compare alternatives Embed widget Claim this listing

Install Scholar

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "scholar": {
      "command": "uvx",
      "args": [
        "scholar-academic-mcp"
      ],
      "env": {
        "SCOPUS_API_KEY": "YOUR_VALUE_HERE",
        "S2_API_KEY": "YOUR_VALUE_HERE",
        "SCIHUB_MIRRORS": "YOUR_VALUE_HERE",
        "LIBGEN_MIRRORS": "YOUR_VALUE_HERE",
        "SCOPUS_INST_TOKEN": "YOUR_VALUE_HERE",
        "CONTACT_EMAIL": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

The scholar MCP server connects AI agents with Scopus, OpenAlex, Semantic Scholar, Unpaywall, book catalogs, and citation services. It supports paper and author discovery, metadata lookup, citation tracking, book searches, DOI resolution, PDF or HTML extraction, and page rendering for vision-capable models. Reach for it when an agent needs structured academic research workflows rather than a single database query. Scopus and OpenAlex provide the main paper-routing paths, while Semantic Scholar, Unpaywall, CrossRef, Google Books, Open Library, and other sources cover additional retrieval tasks.

Use cases

  • Search recent papers across Scopus, OpenAlex, and Semantic Scholar
  • Resolve authors and compare bibliometric profiles
  • Trace citations and related research works
  • Extract text or page images from accessible research PDFs
  • Generate formatted citations and BibTeX records

Key features

  • Multi-source paper and metadata search
  • Author disambiguation and bibliometric profiles
  • Citation and related-work discovery
  • Open-access DOI and PDF resolution
  • PDF text extraction and visual rendering
  • Book search and targeted content extraction

Tools27

What Scholar lets your agent do. Expand a tool for its parameters.

Self-reported~645 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 2d ago

Recent health check succeeded.

6/6 checks healthy over the last 40d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 12d ago via OSV.dev · scholar-academic-mcp (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

Last commit5mo agoMost recent push to the default branch.
Tools exposed27Callable tools this server registers over MCP.
Directory activity1 viewsConfig copies, upvotes, and views on AllMCPs.

How Scholar works

What scholar does

The scholar MCP server exposes academic research and book-retrieval functions through the Model Context Protocol. It gives an AI agent access to paper search, paper metadata, author identification, bibliometric profiles, citation relationships, topic exploration, book metadata, and document-content extraction.

Paper searches can use Scopus Boolean queries or OpenAlex, with sorting by citation count or publication year. Semantic Scholar provides a separate search path and can return AI-generated TLDRs when configured. Metadata lookup accepts identifiers such as DOI, Scopus ID, OpenAlex ID, or Semantic Scholar ID, depending on the tool. Batch lookup supports up to 50 DOIs per request.

The server also handles open-access discovery and content processing. It can search Unpaywall by title, resolve DOI locations, download an open-access PDF, extract text, and render PDF pages as images. HTML pages are supported by the full-text extraction path. Book functions cover Google Books, Open Library, and Library Genesis searches, including targeted extraction from retrieved books.

How it works

An MCP-compatible client starts the server as a local process and sends tool calls over MCP. The server routes requests to external APIs and services, then returns structured results to the agent. Paper and author requests may use different providers based on the identifier or selected search path.

For document analysis, the server checks available access routes, retrieves an accessible PDF or HTML page, and passes content through text or visual extraction. The visual tool renders selected PDF pages as PNG images for models that can inspect images. Closed-access material may require manual handling, according to the project’s access workflow.

The scholar MCP server includes fallback-oriented paths for DOI resolution and PDF retrieval. Its Semantic Scholar search is limited to one request per second. Sci-Hub and Library Genesis tools are included for resolving or retrieving material from those services; their use may have legal, licensing, or policy implications and should be evaluated by the operator.

Setup and configuration

Install the package from PyPI with pip install scholar-academic-mcp, or clone the repository and install it in editable mode with pip install -e . inside a virtual environment. The documented client configuration uses the scholar-academic-mcp command as a stdio MCP server.

SCOPUS_API_KEY and CONTACT_EMAIL are required by the documented configuration. S2_API_KEY enables Semantic Scholar API access for TLDRs and graph functions. SCOPUS_INST_TOKEN is optional and supports fuller Scopus abstract access. SCIHUB_MIRRORS and LIBGEN_MIRRORS accept comma-separated mirror URLs for their respective retrieval tools.

Claude Desktop and Cursor are explicitly documented as configuration targets. The repository identifies Python 3.10 or newer as the supported Python version.

Tools and capabilities

  • Search papers through Scopus, OpenAlex, or Semantic Scholar.
  • Retrieve paper metadata, abstracts, related works, references, and forward citations.
  • Resolve authors by name or ORCID and retrieve OpenAlex, Scopus, or Semantic Scholar profiles.
  • Explore research topics, domains, concepts, and publication-volume information.
  • Search books and retrieve descriptions, editions, and ISBNs.
  • Extract book tables of contents, keyword matches, or selected page ranges.
  • Extract text from OA PDFs or HTML pages and render PDF pages for visual analysis.
  • Generate BibTeX entries and format citations in APA, IEEE, Chicago, Harvard, Vancouver, MLA, or Turabian styles.

Limitations and notes

Provider coverage and fields depend on the upstream service and the credentials supplied. Scopus features require an API key, Semantic Scholar requests are rate-limited to one per second, and full Scopus abstracts may require an institutional token. Unpaywall focuses on open-access locations, while access to closed material is not guaranteed. The repository also documents a Semantic Scholar API key as optional, but some Semantic Scholar capabilities depend on it.

Read the full README View source on GitHub

Reviews

No reviews yet — be the first to share how it worked for you.

Frequently Asked Questions about Scholar

scholar is an MCP server that connects AI agents to Scopus, OpenAlex, Semantic Scholar, Unpaywall, book catalogs, and citation services. Its main tools search papers, retrieve metadata, resolve authors, trace citations, extract PDF or HTML text, render PDF pages, search books, and format citations for research workflows.

Install it from PyPI with `pip install scholar-academic-mcp`. For development, clone the repository, create a Python 3.10+ virtual environment, and run `pip install -e .` from the project directory.

`SCOPUS_API_KEY` and `CONTACT_EMAIL` are required in the documented configuration. `S2_API_KEY`, `SCOPUS_INST_TOKEN`, `SCIHUB_MIRRORS`, and `LIBGEN_MIRRORS` are optional and enable additional provider access or retrieval paths.

Yes, Cursor is explicitly documented as a supported configuration target. Add the server as `scholar-academic-mcp` in the client’s MCP configuration and provide the required environment variables.

Yes, it can extract text from accessible PDF or HTML sources and render selected PDF pages as images. The Unpaywall workflow can resolve a DOI, download an open-access PDF, and pass it to the text extractor.

Related MCP servers

All in Research All alternatives
Add a badge to your READMEShow it’s listed — live SVG, Markdown or HTML.

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:
Live Dynamic SVG PreviewScholar AllMCPs Directory Badge
Markdown (GitHub README)
[![AllMCPs](https://allmcps.com/api/badge/scholar?style=directory)](https://allmcps.com/mcp/scholar)
HTML Embed
<a href="https://allmcps.com/mcp/scholar"><img src="https://allmcps.com/api/badge/scholar?style=directory" alt="Scholar on AllMCPs" /></a>