Allows searching and fetching metadata of academic papers from arXiv.
Allows searching and fetching metadata of academic papers from Google Scholar.
Allows searching and fetching metadata of academic papers from PubMed.
Allows searching and fetching metadata of academic papers from Semantic Scholar.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@aigroup-paper-mcp search for papers about large language models"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Academic paper search and retrieval MCP server integrating multiple scholarly platforms into a unified interface.
aigroup-paper-mcp provides a unified MCP interface for searching, retrieving, and organizing academic paper metadata across major scholarly sources.
It is designed for:
cross-platform academic paper search
paper metadata retrieval and browsing
literature review assistance
research gap analysis and comparison workflows
integration with Claude Desktop and other MCP-compatible clients
Related MCP server: scholar-toolkit-mcp
12+ academic platforms integrated behind one MCP interface
6 advanced tools for search, fetch, discovery, and trend analysis
3 resource patterns for direct metadata and category access
3 prompt templates for literature-review-style workflows
structured responses, caching, and parallel search support
The server currently supports sources such as:
arXiv
OpenAlex
PubMed Central (PMC)
Europe PMC
bioRxiv
medRxiv
CORE
Semantic Scholar
Crossref
PubMed
Google Scholar
IACR
Node.js >= 18
npm
git clone https://github.com/jackdark425/aigroup-paper-mcp.git
cd aigroup-paper-mcp
npm install
npm run build
npm startnpx aigroup-paper-mcp --help
npx aigroup-paper-mcp search "machine learning"
npx aigroup-paper-mcp fetch "2301.00001" --source arxiv{
"mcpServers": {
"aigroup-paper-mcp": {
"command": "npx",
"args": ["aigroup-paper-mcp"]
}
}
}search_papersCross-platform paper search with smart source selection and query optimization.
fetch_paperFetches detailed metadata for a paper by source and identifier.
fetch_latestGets the latest papers from a selected source/category.
list_categoriesLists supported categories for a given platform.
advanced_searchSupports more complex boolean-style academic search queries.
trend_analysisAnalyzes topic evolution and publication trends over time.
paper://{source}/{id}
category://{source}/{category}
search://{query}
literature_review
research_gap_analysis
paper_comparison
Create a .env file if needed:
LOG_LEVEL=info
CACHE_ENABLED=true
CACHE_TTL=3600
MAX_SEARCH_LIMIT=100aigroup-paper-mcp/
├── src/
├── docs/
├── scripts/
├── package.json
└── README.mdnpm run build
npm run test
npm run lintThis project is released under the MIT License.
You may use, copy, modify, merge, publish, distribute, sublicense, and sell copies of this software, including in academic, internal, and commercial contexts, provided that the original copyright notice and license text are preserved.
Please keep in mind:
the software is provided "AS IS", without warranty of any kind
you must retain the relevant copyright and permission notice in copies or substantial portions of the software
downstream usage remains subject to the terms, rate limits, metadata rules, and access restrictions of upstream academic data providers
See the full text in LICENSE.
Thanks to the academic and open metadata ecosystems that make federated retrieval possible, including arXiv, OpenAlex, PubMed, Crossref, Semantic Scholar, and related services.
Model Context Protocol SDK
Repository: https://github.com/modelcontextprotocol/servers
Role: MCP server integration and tool/resource/prompt model
具有布尔运算符（AND、OR、NOT）、模糊匹配和精确匹配功能的高级搜索。
Inputs: query (required), sources, field, fuzzyMatch, +3 more. Returns: results, total
从特定类别的平台获取最新论文。具有智能缓存和摘要模式功能。
Inputs: source (required), category, limit, useCache, +2 more. Returns: papers, total, category
从指定平台根据ID获取论文的详细信息。返回完整的元数据。
Inputs: id (required), source (required). Returns: paper
列出一个或所有平台的可用类别/主题。
Inputs: source. Returns: categories
管理学术论文搜索的缓存系统，包括查看缓存内容、获取缓存项、清理缓存和获取统计信息。
Inputs: action (required), key, pattern, namespace. Returns: action, message, totalKeys, filteredKeys, +9 more
跨多个学术平台搜索论文（arXiv、OpenAlex等）。支持多字段搜索、过滤和排序。
Inputs: query (required), sources, field, categories, +4 more. Returns: results, total, sources
基于语义相似度在缓存中查找相关文献数据，即使查询内容不完全相同也能找到相关结果。
Inputs: query (required), similarityThreshold, maxResults, includeExpired. Returns: action, query, totalKeys, validKeys, +5 more
分析特定主题随时间的变化趋势，包括增长率、高峰期和关键词分析。
Inputs: topic (required), sources, period, granularity, +1 more. Returns: trends, topic, totalPapers
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
Scored across 8 tools
All tools have clearly distinct purposes: advanced_search vs search_papers differ in syntax capabilities, smart_cache_search targets cache semantic search, and others are unique operations. No overlapping responsibilities.
All tool names follow a consistent snake_case pattern with imperative verbs (fetch, list, manage, search) or compound nouns, no mixing of conventions.
8 tools is appropriate for a paper MCP server, covering search, retrieval, cache management, and trend analysis without being too sparse or bloated.
Core functionalities like searching (basic, advanced, semantic), fetching, categories, and trends are covered. Minor gaps include lack of direct PDF retrieval or citation networking, but the surface is comprehensive for typical academic paper search.
Academic research MCP server for paper search, citation checks, graphs, and deep research.
Multi-engine scholarly research server for search, traversal, full text, and reading lists.
Academic paper search, scientific literature, citation analysis, arXiv & semantic related-work.
Personal knowledge base MCP server with semantic search, auto-categorization, metadata extraction
