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AMiner

scipenai

by scipenai

Search AMiner's scholarly article database to find peer reviewed articles by keyword, author, or venue for advanced acad

Integrates with AMiner's academic database to provide paper search by keyword, venue, author, or advanced multi-criteria queries with configurable pagination and sorting options for literature discovery and research workflows.

github stars

8

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Requires AMiner API keySupports Chinese and English interfacesBuilt-in AI assistant prompts for research

best for

  • / Academic researchers conducting literature reviews
  • / Students writing research papers or theses
  • / Scientists tracking publications in their field
  • / Research assistants gathering paper collections

capabilities

  • / Search papers by keyword
  • / Find papers by specific authors
  • / Browse papers from specific journals or conferences
  • / Run advanced multi-criteria searches
  • / Sort results by year or citation count
  • / Paginate through large result sets

what it does

Searches academic papers from AMiner's database using keywords, authors, venues, or advanced multi-criteria queries. Provides detailed paper information with configurable pagination and sorting.

about

AMiner is a community-built MCP server published by scipenai that provides AI assistants with tools and capabilities via the Model Context Protocol. Search AMiner's scholarly article database to find peer reviewed articles by keyword, author, or venue for advanced acad It is categorized under search web.

how to install

You can install AMiner in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

AMiner is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

AMiner MCP 服务器

语言 / Language: 🇨🇳 中文 | 🇺🇸 English

基于模型上下文协议(MCP)的服务器,通过 AMiner API 提供强大的学术论文搜索和分析功能。

🌟 功能特性

🔍 搜索工具

  • 关键词搜索 (search_papers_by_keyword) - 通过关键词搜索论文
  • 期刊搜索 (search_papers_by_venue) - 搜索特定期刊/会议的论文
  • 作者搜索 (search_papers_by_author) - 搜索特定作者的论文
  • 高级搜索 (search_papers_advanced) - 多条件组合搜索

🤖 AI 助手

  • 论文搜索助手 (paper_search_assistant) - 学术研究辅助的 AI 提示模板

⚙️ 搜索选项

  • 分页支持(页码、每页数量)
  • 排序选项(按年份或引用数)
  • 详细论文信息展示
  • 专业学术格式的英文界面

🔧 MCP 客户端配置

添加到您的 MCP 客户端配置文件:

{
  "mcpServers": {
    "aminer": {
      "command": "npx",
      "args": ["-y", "@scipen/aminer-mcp-server"],
      "env": {
        "AMINER_API_KEY": "YOUR_AMINER_API_KEY"
      }
    }
  }
}

🚀 手动运行

# 设置您的 AMiner API 密钥:
export AMINER_API_KEY="your_aminer_api_key_here"
# 使用 npx 启动
npx -y @scipen/aminer-mcp-server

📚 工具列表

search_papers_by_keyword

通过关键词搜索学术论文。

参数:

  • keyword (字符串,必需): 搜索关键词
  • page (数字,可选): 页码,默认 0
  • size (数字,可选): 每页论文数,默认 10,最大 10
  • order (字符串,可选): 排序方式:'year' 或 'n_citation'

示例:

{
  "keyword": "深度学习",
  "page": 0,
  "size": 5,
  "order": "n_citation"
}

search_papers_by_venue

搜索特定期刊/会议发表的论文。

参数:

  • venue (字符串,必需): 期刊/会议名称
  • page (数字,可选): 页码,默认 0
  • size (数字,可选): 每页论文数,默认 10,最大 10
  • order (字符串,可选): 排序方式:'year' 或 'n_citation'

示例:

{
  "venue": "Nature",
  "page": 0,
  "size": 10,
  "order": "year"
}

search_papers_by_author

搜索特定作者发表的论文。

参数:

  • author (字符串,必需): 作者姓名
  • page (数字,可选): 页码,默认 0
  • size (数字,可选): 每页论文数,默认 10,最大 10
  • order (字符串,可选): 排序方式:'year' 或 'n_citation'

示例:

{
  "author": "Geoffrey Hinton",
  "page": 0,
  "size": 10
}

search_papers_advanced

支持多条件的高级搜索。

参数:

  • keyword (字符串,可选): 搜索关键词
  • venue (字符串,可选): 期刊/会议名称
  • author (字符串,可选): 作者姓名
  • page (数字,可选): 页码,默认 0
  • size (数字,可选): 每页论文数,默认 10,最大 10
  • order (字符串,可选): 排序方式:'year' 或 'n_citation'

注意: 必须提供 keyword、venue 或 author 中的至少一个。

示例:

{
  "keyword": "自然语言处理",
  "author": "Yann LeCun",
  "page": 0,
  "size": 5,
  "order": "n_citation"
}

🎯 提示模板

paper_search_assistant

学术研究的 AI 助手提示模板。

参数:

  • research_topic (字符串,必需): 研究主题或领域
  • search_focus (字符串,可选): 搜索重点
    • recent: 关注最新论文
    • highly_cited: 关注高引用论文
    • comprehensive: 平衡搜索(默认)

示例:

{
  "research_topic": "计算机视觉中的注意力机制",
  "search_focus": "highly_cited"
}

🛠️ 开发

项目结构

src/
├── index.ts          # 主服务器文件
├── aminer-client.ts  # AMiner API 客户端
└── types.ts          # 类型定义

可用脚本

  • pnpm run build - 构建项目
  • pnpm run start - 启动服务
  • pnpm run dev - 开发模式
  • pnpm run lint - 代码检查
  • pnpm test - 运行测试

技术栈

  • 运行时: Node.js 18+
  • 语言: TypeScript
  • 框架: Model Context Protocol SDK
  • 包管理器: pnpm
  • API: AMiner 开放平台 API
  • 协议: JSON-RPC 2.0 (MCP)

📄 许可证

MIT 许可证

🤝 贡献

欢迎提交 Issues 和 Pull Requests!

📞 支持

如有问题和支持需求, 请添加小助手的企业微信:

<img src="qrcode.jpg" alt="企业微信二维码" width="200" />

FAQ

What is the AMiner MCP server?
AMiner is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for AMiner?
This profile displays 38 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Web Research & Information Gathering

Fetch and extract information from websites automatically

Example

Research competitor pricing, scrape product reviews, monitor news mentions

Automate 5-10 hours/week of manual web research

Content Monitoring & Alerts

Track website changes, new content, price updates

Example

Monitor competitor blog for new posts, track stock availability, watch for pricing changes

Stay informed without manual checking, never miss important updates

Data Extraction & Aggregation

Extract structured data from multiple websites

Example

Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data

Build datasets 100x faster than manual copying

API-less Integration

Interact with services that don't offer APIs

Example

Check form submissions, validate website functionality, test user flows

Automate interactions with any website, even without API

Implementation Guide

Prerequisites

  • Claude Desktop or Cursor with MCP support
  • Understanding of web scraping ethics and robots.txt
  • Rate limiting awareness to avoid overwhelming target sites
  • Knowledge of legal restrictions on data collection

Time Estimate

20-40 minutes including configuration and testing

Installation Steps

  1. 1.Install web automation MCP server via npm or pip
  2. 2.Configure allowed domains and rate limits in MCP config
  3. 3.Test with simple fetch: 'Get content from example.com'
  4. 4.Progress to extraction: 'Extract all product prices from this page'
  5. 5.Set up monitoring: 'Check this URL daily for changes'
  6. 6.Parse structured data: 'Create CSV from this table'
  7. 7.Respect robots.txt and rate limits always

Troubleshooting

  • 403 Forbidden: Website blocks bots—respect their wishes, use official API instead
  • Rate limit errors: Slow down requests, add delays between fetches
  • Stale data: Target site changed HTML structure—update selectors
  • Timeout errors: Site is slow or blocking—increase timeout, try different user agent
  • JavaScript-rendered content: Use headless browser MCP servers for dynamic sites

Best Practices

✓ Do

  • +Check robots.txt and respect crawl rules
  • +Rate limit requests: 1-2 requests/second maximum
  • +Use official APIs when available instead of scraping
  • +Identify your bot with descriptive user agent
  • +Cache results to minimize repeated requests
  • +Handle errors gracefully with retries and fallbacks
  • +Validate extracted data for accuracy

✗ Don't

  • Don't scrape sites that explicitly forbid it (robots.txt, ToS)
  • Don't overwhelm servers with rapid requests—use rate limiting
  • Don't scrape personal data without consent and legal basis
  • Don't ignore copyright on extracted content
  • Don't assume HTML structure is stable—handle changes
  • Don't use scraped data for commercial purposes without permission

💡 Pro Tips

  • Use CSS selectors or XPath for robust data extraction
  • Set up monitoring alerts for extraction failures (structure changed)
  • Implement exponential backoff for retries on failures
  • Store raw HTML for reprocessing if extraction logic changes
  • Combine with data analysis tools for insights from extracted data
  • Consider using official APIs or RSS feeds as more stable alternatives

Technical Details

Architecture

MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.

Protocols

  • HTTP/HTTPS
  • WebSocket (for real-time sites)
  • Puppeteer/Playwright (for JavaScript sites)

Compatibility

  • Static HTML sites
  • JavaScript-rendered SPAs (with headless browser)
  • REST APIs
  • GraphQL endpoints

When to Use This

✓ Use When

Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.

✗ Avoid When

Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.

Integration

  • Scheduled monitoring with change detection
  • Multi-source data aggregation pipelines
  • Fallback to web scraping when API rate limits hit
  • Headless browser for JavaScript-heavy sites

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.638 reviews
  • Ganesh Mohane· Dec 28, 2024

    Strong directory entry: AMiner surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Layla Ghosh· Dec 12, 2024

    AMiner has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Shikha Mishra· Dec 8, 2024

    According to our notes, AMiner benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Ira Zhang· Dec 8, 2024

    Useful MCP listing: AMiner is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Mei Okafor· Nov 27, 2024

    AMiner is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Sakshi Patil· Nov 19, 2024

    AMiner is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • James Lopez· Oct 18, 2024

    We wired AMiner into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Chaitanya Patil· Oct 10, 2024

    We evaluated AMiner against two servers with overlapping tools; this profile had the clearer scope statement.

  • Tariq Kapoor· Sep 17, 2024

    Strong directory entry: AMiner surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Emma Thomas· Sep 9, 2024

    AMiner has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

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