What are the Semantic Scholar API rate limits?
The API allows up to 100 requests per 5 minutes. To access a higher rate limit, visit Semantic Scholar to request authentication for your project.
@hamid-vakilzadeh
Basic information
Semantic Scholar MCP
No standard config provided
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AI - Research Assistant is a Model Context Protocol (MCP) server that provides AI models with comprehensive access to the Semantic Scholar Academic Graph API. It enables intelligent literature search, paper analysis, and citation network exploration through a set of tools, resources, and prompts. This server is intended for researchers and developers who want to integrate academic research capabilities into AI‑powered workflows.
Install Node.js, then install the MCP server and restart your AI platform (e.g., Claude Desktop). Obtain a Semantic Scholar API key (optional but recommended for higher rate limits) and set it as the environment variable SEMANTIC_SCHOLAR_API_KEY. Finally, deploy using your preferred MCP client or integration platform.
The API allows up to 100 requests per 5 minutes. To access a higher rate limit, visit Semantic Scholar to request authentication for your project.
Tools include `papers-search-basic`, `papers-search-advanced`, `papers-match`, `papers-get`, `papers-batch`, `papers-citations`, `papers-references`, `authors-search`, `authors-papers`, and `analysis-citation-network`.
Yes, three prompts are available: `literature-review` (systematic review with trend analysis), `citation-analysis` (impact assessment), and `research-gap-finder` (identify unexplored opportunities).
The MCP extends the work of an academic paper on using retrieval‑augmented generation (RAG) as a research assistant. While MCP is not covered in the paper, it continues the same effort and reflects lessons learned.
The server requires Node.js to be installed. An optional Semantic Scholar API key can be set via the environment variable `SEMANTIC_SCHOLAR_API_KEY` to obtain higher rate limits.

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