Academia
Automate scientific research workflows by providing tools to search, fetch, analyze, and report on academic papers and datasets.
About
Academia is an MCP server designed to streamline and automate scientific research processes. It offers a comprehensive suite of tools for interacting with various academic resources, including ArXiv, ACL Anthology, Hugging Face datasets, and Semantic Scholar for citations. Researchers and automated agents can leverage its capabilities for web search, webpage crawling, LaTeX compilation, and PDF content extraction. The server also supports optional integration with Large Language Models (LLMs) to power advanced functionalities such as document question answering, scientific paper reviews, and sophisticated research proposal generation and scoring workflows, making it a powerful tool for accelerating discovery.
Key Features
- Access to leading academic databases (ArXiv, ACL Anthology, Hugging Face Datasets, Semantic Scholar).
- Integrated web search and webpage crawling for comprehensive information gathering.
- Advanced document processing, including LaTeX compilation and PDF content extraction.
- Optional LLM-powered tools for document Q&A and research proposal workflows.
- Flexible deployment options, including HTTP, stdio transport, and Docker containerization.
- 15 GitHub stars
Use Cases
- Automating literature reviews and scientific information retrieval for LLM agents.
- Developing tools for automated drafting, scoring, and analysis of research proposals.
- Building custom data pipelines to aggregate and analyze scientific papers and datasets.
