Adamamer20 Paper Search Mcp Openai

ai.smithery由 smithery.ai 发布官方发布者v1.14.0更新于 Oct 24, 2026

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

发布方自己的服务:222wcnm Bilistalkermcp

已验证Streamable HTTP可网页运行网页搜索与抓取知识与记忆

概览

AI 生成的概览

让助手在 arXiv、PubMed、bioRxiv、medRxiv、Google Scholar、IACR 和 Semantic Scholar 上搜索并下载学术论文。

可以做什么
  • 在 arXiv、PubMed、bioRxiv、medRxiv、Google Scholar、IACR ePrint 和 Semantic Scholar 上检索学术论文
  • 从支持的来源下载论文 PDF
  • 以统一的论文格式返回结果,便于放入大模型上下文
  • 提供标准化的 search 与 fetch 工具,供 OpenAI Deep Research 和 ChatGPT 连接器使用
适用场景
适合需要助手查找文献、收集参考文献或下载论文 PDF 的研究与 AI 驱动文献工作流程。
运行要求
通过 streamable HTTP 连接 server.smithery.ai 的远程端点,需 OAuth 认证和 Authorization bearer 令牌。上游项目是 Python 包,也可用 uv 或 pip 本地运行;可选的 SEMANTIC_SCHOLAR_API_KEY 可启用增强的 Semantic Scholar 功能。需要能访问各论文来源的网络。
安装前请注意
README 将 Sci-Hub 列为可选来源,可能涉及法律或授权问题,请确认启用了哪些来源。搜索查询和下载请求会发送到第三方学术网站。Authorization bearer 令牌属于机密,不应外泄。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Adamamer20 Paper Search Mcp Openai,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/ai.smithery%2Fadamamer20-paper-search-mcp-openai/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

{
  "mcpServers": {
    "adamamer20-paper-search-openai": {
      "type": "http",
      "url": "https://server.smithery.ai/@adamamer20/paper-search-mcp-openai/mcp"
    }
  }
}

README

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

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:

bash
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):

    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 installedcurl -LsSf https://astral.sh/uv/install.sh | sh
    # Clone repositorygit clone https://github.com/openags/paper-search-mcp.gitcd paper-search-mcp
    # Create and activate virtual environmentuv venvsource .venv/bin/activate  # On Windows: .venv\Scripts\activate
  2. Install Dependencies:

    bash
    # Install project in editable modeuv 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.gitcd paper-search-mcppip 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.

来源:README.md,提交 671f572

工具

0
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版本历史

1
  1. v1.14.0最新Sep 16, 2026

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