AI Research Assistant
Unverified verified 13 jun 2026TL;DR
A Model Context Protocol (MCP) server that connects AI agents to Semantic Scholar and arXiv for real-time academic research. It is designed for researchers and developers who need LLMs to perform grounded literature searches, citation analysis, and full-text PDF extraction. Its key differentiator is the ability to fetch full-text content from arXiv and Wiley open-access sources without requiring an upfront API key.
What Users Actually Pay
No user-reported pricing yet.
Our Take
AI Research Assistant occupies a vital niche in the burgeoning 'Agentic AI' ecosystem by serving as a standardized bridge between LLMs and peer-reviewed data. While many RAG (Retrieval-Augmented Generation) tools rely on static vector databases, this tool provides dynamic, live access to over 200 million papers via the Semantic Scholar Graph API. It effectively solves the 'hallucination' problem in academic workflows by forcing the AI to cite and analyze actual available metadata. The tool is technically an open-source implementation of the Model Context Protocol, making it natively compatible with leading AI IDEs like Cursor and Claude Desktop. Its strength lies in its specialized toolset, which includes citation network analysis and batch operations that are often restricted behind paid tiers in commercial research software. However, because it is an open-source project rather than a managed service, it requires users to handle their own local setup via Node.js or Docker. It is best suited for academic researchers, graduate students, and developers building specialized AI agents for science. While it functions without an API key, serious users will find the default rate limits of Semantic Scholar's public tier restrictive for large-scale literature reviews, necessitating a free API key request for higher throughput.
Similar Products
Pros
- + Zero-friction start with no mandatory API key for basic academic searches.
- + Support for full-text PDF extraction from arXiv and Wiley open-access sources.
- + Comprehensive citation analysis tools, including h-index retrieval and citation graph exploration.
- + Seamless integration with MCP-compatible hosts like Claude Desktop and Cursor.
- + Open-source and highly customizable for specific research workflows.
Cons
- - Requires technical setup (Node.js/Docker), which may be a barrier for non-technical academics.
- - Subject to Semantic Scholar's public rate limits (100 requests per 5 minutes) without an authenticated key.
- - PDF extraction is limited to specific open-access repositories (arXiv/Wiley).
- - Maintenance is community-driven, leading to potential lag in supporting API changes from data providers.
Sentiment Analysis
Sentiment has improved since last capture. The sentiment has significantly improved from 0.00 to 0.86 as the product has gained substantial traction within the MCP developer community. It is widely praised for its utility in academic grounding, with high tool-call volumes indicating it is a 'standard' choice for research-oriented AI setups.
Sentiment Over Time
By Source
21480 mentions
Sample quotes (1)
- "The server provides immediate access to millions of academic papers... enabling AI-powered research with comprehensive search and citation analysis."
45 mentions
Sample quotes (1)
- "This server enables intelligent literature search, paper analysis, and citation network exploration through a robust set of tools."
12 mentions
Sample quotes (1)
- "If you are doing research in Claude, the Semantic Scholar MCP server is a must-have for getting real citations instead of made-up ones."
Agent Readiness
51/100AI Research Assistant is 'Agent-First' by design, built specifically for the Model Context Protocol. It provides a standardized interface that allows AI agents to autonomously search, fetch, and analyze academic data. While it lacks traditional SaaS integrations like Zapier, it is natively compatible with the next generation of AI-native platforms (Claude, Cursor, n8n via MCP), making it one of the most 'agent-ready' research tools available.
Last checked May 10, 2026
MCP Integrations
2 servers12 tools32,213 total usesThe server provides immediate access to millions of academic papers through Semantic Scholar and arXiv, enabling AI-powered research with comprehensive search, citation analysis, and full-text PDF extraction from multiple sources (arXiv and Wiley open-access). - No API key is required.
12 tools
papers-search-basicSearch for academic papers with a simple query.paper-search-advancedSearch for academic papers with advanced filtering optionssearch-paper-titleFind a paper by closest title matchget-paper-abstractGet detailed information about a specific paper including its abstractpapers-citationsGet papers that cite a specific paperpapers-referencesGet papers cited by a specific paperauthors-searchSearch for authors by name or affiliationauthors-papersGet papers written by a specific authorpapers-batchLook up multiple papers by their IDssearch-arxivSearch for papers on arXiv using their APIdownload-full-paper-arxivDownload full-text PDF of an arXiv paper and extract text content (memory only)analysis-citation-networkAnalyze the citation network for a specific paper
12 tools
papers-search-basicSearch for academic papers with a simple query.paper-search-advancedSearch for academic papers with advanced filtering optionssearch-paper-titleFind a paper by closest title matchget-paper-abstractGet detailed information about a specific paper including its abstractpapers-citationsGet papers that cite a specific paperpapers-referencesGet papers cited by a specific paperauthors-searchSearch for authors by name or affiliationauthors-papersGet papers written by a specific authorpapers-batchLook up multiple papers by their IDssearch-arxivSearch for papers on arXiv using their APIdownload-full-paper-arxivDownload full-text PDF of an arXiv paper and extract text content (memory only)analysis-citation-networkAnalyze the citation network for a specific paper
Last checked May 26, 2026
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