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Semanticscholar MCP Server
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Semanticscholar MCP Server

This project implements an MCP server that interacts with the Semantic Scholar API, providing functions such as paper search, obtaining paper/author details, and querying cited literature.
Research and dataSearch tools#Academic search#Paper query#Literature citation.Python
2.5 points
11.2K
Open Site

Overview

Installation

Content Details

Alternatives

What is the Semantic Scholar MCP Server?

This is an intelligent academic assistant service that integrates the functions of the Semantic Scholar academic database into AI chat tools through the Model Context Protocol (MCP) technology. It allows you to directly query academic papers, author information, and literature citation networks in the chat interface.

How to use the Semantic Scholar service?

You can directly use this service through AI tools such as Claude, Cursor, or Windsurf without writing code. Simply describe your needs in natural language, such as 'Help me find recent papers on deep learning', and the system will automatically process the query and return the results.

Applicable scenarios

This service is particularly suitable for researchers, students, and anyone who needs to quickly access academic information. Typical scenarios include literature reviews, tracking the latest developments in the field, finding the works of specific authors, and analyzing paper citation networks.

Main features

Academic paper search
Search for academic papers in the Semantic Scholar database by conditions such as keywords, authors, and publication years.
Obtain paper details
Get the complete information of a specific paper, including the abstract, author list, publication information, etc.
Query author information
Find the research fields, publication records, and collaboration networks of specific scholars.
Citation relationship analysis
View the citation and being - cited situations of papers to understand academic influence.
Advantages
No programming knowledge is required, and it can be used through natural language.
It is directly integrated into commonly used AI tools, making it convenient to use.
Access the complete academic database of Semantic Scholar.
Quickly obtain structured academic information.
Limitations
The query results are limited by the coverage of the Semantic Scholar database.
Complex queries may require multiple interactions.
The full - text content behind the paywall cannot be directly accessed.

How to use

Install the service
Select an appropriate installation method according to the client you are using (Claude/Cursor/Windsurf).
Start the query
Directly enter your query requirements in the chat interface, for example, 'Help me find the latest papers on the interpretability of neural networks'.
Optimize the results
Based on the initial results, you can further refine the query conditions, such as specifying the year, author, or journal.

Usage examples

Literature review assistance
When preparing a literature review on 'Transformer applications in computer vision', quickly obtain important papers in the relevant field.
Track scholars' research
Keep track of the latest research work of a certain scholar.
Citation network analysis
Understand the academic influence of a pioneering paper.

Frequently Asked Questions

Is this service paid?
What's the difference between the query results and searching directly on the Semantic Scholar website?
Why can't some papers be found?
Can I get the full - text of papers?

Related resources

Semantic Scholar official website
The official academic search engine website.
MCP protocol documentation
Technical specification of the Model Context Protocol.
Installation guide video
Step - by - step installation demonstration.

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "semanticscholar": {
      "command": "python",
      "args": ["-m", "semanticscholar_mcp_server"]
      }
  }
}

{
  "mcpServers": {
    "semanticscholar": {
      "command": "C:\\Users\\YOUR\\PATH\\miniconda3\\envs\\mcp_server\\python.exe",
      "args": [
        "D:\\code\\YOUR\\PATH\\semanticscholar-MCP-Server\\semanticscholar_server.py"
      ],
      "env": {},
      "disabled": false,
      "autoApprove": []
    }
  }
}

{
  "mcpServers": {
    "semanticscholar": {
      "command": "bash",
      "args": [
        "-c",
        "source /home/YOUR/PATH/.venv/bin/activate && python /home/YOUR/PATH/semanticscholar_mcp_server.py"
      ],
      "env": {},
      "disabled": false,
      "autoApprove": []
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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