IlyaGusev/academia_mcp
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Academia MCP is a collection of tools designed to facilitate the search and retrieval of scientific papers from various academic sources.
Academia MCP is a powerful suite of tools that streamlines the process of searching for and downloading scientific papers from multiple academic databases. It integrates with popular sources such as ArXiv, ACL Anthology, and Semantic Scholar, providing users with a comprehensive platform for academic research. The package is particularly useful for researchers, students, and academics who need to access a wide range of scientific literature efficiently. By leveraging the capabilities of MCP (Model Context Protocol) technology, Academia MCP offers a seamless experience for retrieving papers, exploring citation graphs, and accessing datasets. The tool is easy to install and configure, making it accessible to users with varying levels of technical expertise. With its robust search capabilities and integration with major academic resources, Academia MCP is an invaluable tool for anyone involved in scientific research.
Features
- Seamless integration with major academic databases like ArXiv and ACL Anthology.
- Efficient search and download of scientific papers.
- Access to Semantic Scholar citation graphs for exploring academic networks.
- User-friendly installation and configuration process.
- Support for HuggingFact datasets search.
Usages
usage with Claude Desktop
{
"mcpServers": {
"academia": {
"command": "python3",
"args": [
"-m",
"academia_mcp"
]
}
}
}Tools
ArXiv search and download
Tool for searching and downloading papers from ArXiv.
ACL Anthology search
Tool for searching papers in the ACL Anthology.
HuggingFact datasets search
Tool for searching datasets in HuggingFact.
Semantic Scholar citation graphs
Tool for exploring citation graphs from Semantic Scholar.