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  1. Home
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  3. Adamamer20 Paper Search MCP Openai
Adamamer20 Paper Search MCP Openai logo
Health: ActiveRecent health check succeeded.Last checked 9/21/2026, 4:46:24 PM

Adamamer20 Paper Search MCP Openai

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time — check back soon.
View Repository15 GitHub StarsTotal stargazers on GitHub for the source repository (15 stars).Visit Website

Search and download academic papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, Semantic…

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON ▾
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for adamamer20-paper-search-mcp-openai, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing Alternatives🔬 More in Research

Documentation Overview

Paper Search MCP

A Model Context Protocol (MCP) server for searching and downloading academic papers from multiple sources, including arXiv, PubMed, bioRxiv, and Sci-Hub (optional). Designed for seamless integration with large language models like Claude Desktop.

PyPI License Python smithery badge


Table of Contents

  • Overview
  • Features
  • Installation
    • Quick Start
      • Install Package
      • Configure Claude Desktop
    • For Development
      • Setup Environment
      • Install Dependencies
  • Contributing
  • Demo
  • License
  • TODO

Overview

paper-search-mcp is a Python-based MCP server that enables users to search and download academic papers from various platforms. It provides tools for searching papers (e.g., search_arxiv) and downloading PDFs (e.g., download_arxiv), making it ideal for researchers and AI-driven workflows. Built with the MCP Python SDK, it integrates seamlessly with LLM clients like Claude Desktop.


Features

  • Multi-Source Support: Search and download papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, IACR ePrint Archive, Semantic Scholar.
  • Deep Research Ready: Provides the standardized search and fetch tools required by OpenAI Deep Research and ChatGPT connectors.
  • Standardized Output: Papers are returned in a consistent dictionary format via the Paper class.
  • Asynchronous Tools: Efficiently handles network requests using httpx.
  • MCP Integration: Compatible with MCP clients for LLM context enhancement.
  • Extensible Design: Easily add new academic platforms by extending the academic_platforms module.

Installation

paper-search-mcp can be installed using uv or pip. Below are two approaches: a quick start for immediate use and a detailed setup for development.

Installing via Smithery

To install paper-search-mcp for Claude Desktop automatically via Smithery:

Terminal
npx -y @smithery/cli install @openags/paper-search-mcp --client claude

Quick Start

For users who want to quickly run the server:

  1. Install Package:

    bash
    uv add paper-search-mcp
    
  2. Configure Claude Desktop: Add this configuration to ~/Library/Application Support/Claude/claude_desktop_config.json (Mac) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

    config.json
    {
      "mcpServers": {
        "paper_search_server": {
          "command": "uv",
          "args": [
            "run",
            "--directory",
            "/path/to/your/paper-search-mcp",
            "-m",
            "paper_search_mcp.server"
          ],
          "env": {
            "SEMANTIC_SCHOLAR_API_KEY": "" // Optional: For enhanced Semantic Scholar features
          }
        }
      }
    }
    

    Note: Replace /path/to/your/paper-search-mcp with your actual installation path.

For Development

For developers who want to modify the code or contribute:

  1. Setup Environment:

    bash
    # Install uv if not installed
    curl -LsSf https://astral.sh/uv/install.sh | sh
    
    # Clone repository
    git clone https://github.com/openags/paper-search-mcp.git
    cd paper-search-mcp
    
    # Create and activate virtual environment
    uv venv
    source .venv/bin/activate  # On Windows: .venv\Scripts\activate
    
  2. Install Dependencies:

    bash
    # Install project in editable mode
    uv add -e .
    
    # Add development dependencies (optional)
    uv add pytest flake8
    

Contributing

We welcome contributions! Here's how to get started:

  1. Fork the Repository: Click "Fork" on GitHub.

  2. Clone and Set Up:

    bash
    git clone https://github.com/yourusername/paper-search-mcp.git
    cd paper-search-mcp
    pip install -e ".[dev]"  # Install dev dependencies (if added to pyproject.toml)
    
  3. Make Changes:

    • Add new platforms in academic_platforms/.
    • Update tests in tests/.
  4. Submit a Pull Request: Push changes and create a PR on GitHub.


Demo

Demo

TODO

Planned Academic Platforms

  • [√] arXiv
  • [√] PubMed
  • [√] bioRxiv
  • [√] medRxiv
  • [√] Google Scholar
  • [√] IACR ePrint Archive
  • [√] Semantic Scholar
  • PubMed Central (PMC)
  • Science Direct
  • Springer Link
  • IEEE Xplore
  • ACM Digital Library
  • Web of Science
  • Scopus
  • JSTOR
  • ResearchGate
  • CORE
  • Microsoft Academic

License

This project is licensed under the MIT License. See the LICENSE file for details.


Happy researching with paper-search-mcp! If you encounter issues, open a GitHub issue.

Read the full README →View source on GitHub →

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Adoption & maintenance

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

GitHub stars
15
Stargazers on the source repository.
npm downloads
27k
Package downloads in the last 30 days.
Last commit
1y ago
Most recent push to the default branch.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Adamamer20 Paper Search MCP Openai

We don't have a confirmed install command for adamamer20-paper-search-mcp-openai yet, so we don't publish a generated one — a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/adamamer20/paper-search-mcp-openai) for the current steps.

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Technical Specs & Signals

Category🔬Research
More technical detailsExpand ▾
Last updatedSep 18, 2025
12/12 checks healthy over the last 45d
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars15
GitHub Star CountTotal stargazers on GitHub representing community popularity (15 stars).
Last commit1y ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 18, 2025
npm downloads27,958/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
37Quality signal: Fair · 37/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools12/30
Adoption & activity6/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

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Scanned 26d ago via OSV.dev

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