Semantic Scholar MCP Server
Provides tools for searching and retrieving academic papers, exploring citation graphs, and looking up author profiles using the Semantic Scholar database.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Semantic Scholar MCP ServerSearch for recent papers on protein structure prediction"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Semantic Scholar MCP Server
An MCP server that gives Claude access to Semantic Scholar's database of 200M+ academic papers. Search papers, explore citation graphs, and look up authors — directly from Claude. Wraps the official semanticscholar SDK with a process-wide rate limiter to prevent 429s under concurrent dispatch.
Tools
Tool | Description |
| Keyword search with filters for year range, fields of study, and open-access availability |
| Get full details for a paper by Semantic Scholar ID, DOI, ArXiv ID, or PubMed ID |
| Navigate the citation graph — find papers that cite a given paper, or papers it references |
| Look up an author's profile, h-index, and publication metrics |
| Find an author by name and list their top papers |
Related MCP server: Semantic Scholar MCP Server
Setup
Prerequisites
Python 3.11+
uv (recommended) or pip
A Semantic Scholar API key (see below — strongly recommended)
Get an API key
Without a key, requests share a global anonymous rate-limit bucket and you will see frequent 429 Too Many Requests errors during normal use. Request a free key at semanticscholar.org/product/api — turnaround is usually a few days.
Once you have a key, set it as an environment variable:
export S2_API_KEY=your_key_hereFor persistence across shells, add the line to ~/.zshenv (or your shell's equivalent).
Install
git clone https://github.com/xiuyechen/semantic-scholar-mcp.git
cd semantic-scholar-mcp
uv pip install -e .Or with pip:
pip install -e .Rate limiting and retries
The client wraps the official semanticscholar Python SDK and adds a process-wide async token bucket on top. Concurrent calls from the same process serialize through a 1.05s floor so the client cannot burst past the API's 1 req/sec limit, even when an LLM dispatches multiple tools in parallel. Transient 429s are retried with Retry-After-aware exponential backoff (up to 5 attempts). No tuning required.
Configure with Claude
Claude Code
claude mcp add semantic-scholar -- semantic-scholar-mcpOr with an API key:
claude mcp add semantic-scholar -e S2_API_KEY=your_key -- semantic-scholar-mcpClaude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"semantic-scholar": {
"command": "semantic-scholar-mcp",
"env": {
"S2_API_KEY": "your_key_here"
}
}
}
}Example Usage
Once configured, you can ask Claude things like:
"Search for recent papers on protein structure prediction"
"Find the paper with DOI 10.1038/s41586-021-03819-2 and summarize it"
"What papers cite AlphaFold2? Show me the most influential ones"
"Look up David Baker's publication record"
"Find open-access papers on CRISPR gene editing from 2024"
API Reference
This server wraps the Semantic Scholar Academic Graph API. The API is free to use and covers:
200M+ papers from all major publishers
2.4B+ citation edges
Author profiles with h-index and affiliation data
Open access PDF links where available
AI-generated TLDR summaries for many papers
License
MIT
This server cannot be deployed
Maintenance
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