About Scholar_mcp_server
Scholar_mcp_server is a Go-based MCP server for researchers and others searching academic literature. It searches multiple scholarly sources in parallel, deduplicates and ranks results, and retrieves paper details by identifier.
Key features
- 01Search multiple scholarly databases
- 02Deduplicate by DOI and title
- 03Normalize paper metadata
- 04Search in parallel and rank results
- 05Retrieve paper details by identifier
Use cases
- 01Find papers on a topic across databases
- 02Filter by author, year, or citation count
- 03Look up papers by DOI or arXiv ID
MCP support
It provides MCP clients with tools for aggregated paper search and paper details, querying multiple academic data sources through MCP.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
http://127.0.0.1:8080/mcpclaude mcp add --transport http scholar_mcp_server http://127.0.0.1:8080/mcp{"mcpServers":{"scholar_mcp_server":{"type":"http","url":"http://127.0.0.1:8080/mcp"}}}Open in Cursor{"servers":{"scholar_mcp_server":{"type":"http","url":"http://127.0.0.1:8080/mcp"}}}Open in VS Code{"mcpServers":{"scholar_mcp_server":{"type":"http","url":"http://127.0.0.1:8080/mcp"}}}{"mcpServers":{"scholar_mcp_server":{"serverUrl":"http://127.0.0.1:8080/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project README学术论文检索聚合 MCP 服务
基于 Go 语言实现的学术论文检索聚合 MCP (Model Context Protocol) 服务,通过统一接口同时调用多个学术数据库,提供智能去重、合并和排序的搜索结果。
功能特性
- 🔍 多源聚合搜索: 同时调用6个主要学术数据库
- 🧠 智能去重合并: 基于DOI和标题的智能重复检测
- 📊 统一数据格式: 标准化的论文元数据结构
- 🚀 并发高性能: 异步并行调用所有数据源
- 🎯 精确结果: 智能排序和相关性评分
- 🌐 MCP 协议支持: 完整的MCP工具接口
- 📝 详细状态报告: 实时数据源状态和性能监控
支持的数据源
- arXiv: 物理学、数学、计算机科学预印本 (免费)
- Semantic Scholar: AI驱动的学术搜索引擎 (免费)
- Crossref: 全球最大的DOI注册机构 (免费)
- Scopus: Elsevier学术数据库 (需要API密钥)
- ADSABS: NASA天体物理学数据系统 (需要API密钥)
- Sci-Hub: 学术论文PDF获取 (免费,但需注意法律风险)
可用工具
1. searchScholarPapers - 聚合学术论文搜索
从多个数据源同时搜索学术论文,自动合并去重并排序结果。
参数:
query(string): 搜索关键词(必需)author(string): 作者筛选(可选)title(string): 标题筛选(可选)journal(string): 期刊筛选(可选)year(string): 年份筛选(可选,如"2020-2023")categories([]string): 分类筛选(可选)min_citations(int): 最小引用数(可选)open_access_only(bool): 仅开放获取(可选)offset(int): 偏移量,默认 0limit(int): 限制数量,默认 10,最大 100sort_by(string): 排序方式(relevance, citation_count, published_date)sort_order(string): 排序顺序(asc, desc)enabled_sources([]string): 指定数据源(可选)
基础搜索示例:
{
"query": "machine learning"
}
高级搜索示例:
{
"query": "deep learning",
"author": "Hinton",
"year": "2020-2023",
"min_citations": 100,
"open_access_only": true,
"limit": 20,
"sort_by": "citation_count",
"sort_order": "desc"
}
指定数据源示例:
{
"query": "quantum computing",
"enabled_sources": ["arxiv", "semantic_scholar", "crossref"]
}
2. getScholarPaper - 获取论文详情
根据任意标识符获取特定论文的完整信息,自动选择最佳数据源。
参数:
identifier(string): 论文标识符(必需)
DOI查询示例:
{
"identifier": "10.1038/nature12373"
}
arXiv ID查询示例:
{
"identifier": "2301.07041"
}
安装和运行
环境要求
- Go 1.24+
- 网络连接(访问各学术数据库API)
- 可选:Scopus API密钥
- 可选:ADSABS API密钥
快速启动
- 克隆项目
git clone https://github.com/Seelly/scholar_mcp_server.git
cd scholar_mcp_server
- 安装依赖
go mod tidy
- 基础运行(使用免费数据源)
go run main.go logging.go
完整功能运行
配置API密钥以启用全部功能:
# 设置API密钥
export SCOPUS_API_KEY="your_scopus_api_key"
export ADSABS_API_KEY="your_adsabs_api_key"
# 运行服务器
go run main.go logging.go
生产部署
# 编译二进制文件
go build -o scholar-server main.go logging.go
# 后台运行
nohup ./scholar-server > server.log 2>&1 &
服务器将在 http://127.0.0.1:8080/ 启动。
MCP 客户端配置
Claude Desktop 配置
在 ~/.cursor/mcp.json 或 Claude Desktop 配置文件中添加:
{
"mcpServers": {
"arXiv论文检索服务": {
"url": "http://127.0.0.1:8080/mcp"
}
}
}
使用示例
搜索论文
# 使用 curl 测试搜索功能
curl -X POST http://127.0.0.1:8080/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "searchArxivPapers",
"arguments": {
"query": "deep learning",
"max_results": 5
}
}
}'
获取论文详情
curl -X POST http://127.0.0.1:8080/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "getArxivPaper",
"arguments": {
"id": "2301.07041"
}
}
}'
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.