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Semantic Scholar MCP Server

This powerful MCP server bridges the gap between AI assistants and academic research by providing direct access to Semantic Scholar's comprehensive database. Whether you're conducting literature reviews, exploring citation networks, or seeking academic insights, this server offers a streamlined interface to millions of research papers.

Installation
Add the following to your MCP client configuration file.

Configuration

View docs
{
  "mcpServers": {
    "alperenkocyigit-semantic-scholar-graph-api": {
      "command": "python",
      "args": [
        "server.py"
      ]
    }
  }
}

You set up this MCP server to access Semantic Scholar data through a standardized MCP interface, enabling AI assistants to perform advanced paper searches, author research, citation analysis, and content discovery with low latency and scalable transport.

How to use

You interact with the Semantic Scholar MCP Server using a compatible MCP client. You can search for papers with natural language queries, retrieve detailed paper and author information, explore citation networks, and fetch content snippets when available. Use the available tools to perform bulk lookups, get autocomplete suggestions, and generate AI-powered recommendations based on your input. When you start a session, point your client at the MCP server endpoint and invoke the corresponding tool by its name and parameters. The server supports both traditional search and advanced discovery workflows, so you can combine multiple tools in a single session to build complex literature analyses.

How to install

Prerequisites you need on your system are Python 3.10 or higher and network access to reach the Semantic Scholar API. You will also need a local runtime for the MCP server and a client to connect to it.

Follow these steps to install and run the MCP server locally using the provided Python implementation.

# 1. Clone the project
git clone https://github.com/alperenkocyigit/semantic-scholar-graph-api.git
cd semantic-scholar-graph-api

# 2. Install Python dependencies
pip install -r requirements.txt

# 3. Run the MCP Streamable HTTP server locally
python server.py

Available tools

search_semantic_scholar

Search papers by query and return results for literature discovery.

search_semantic_scholar_authors

Find authors by name to build researcher profiles.

get_semantic_scholar_paper_details

Fetch comprehensive details for a specific paper.

get_semantic_scholar_author_details

Retrieve author profiles and metrics.

get_semantic_scholar_citations_and_references

Obtain the forward and backward citation network for a paper.

get_semantic_scholar_paper_match

Find exact matches for a given paper title or identifier.

get_semantic_scholar_paper_autocomplete

Get intelligent title suggestions as you type.

get_semantic_scholar_papers_batch

Retrieve multiple papers in a single request.

get_semantic_scholar_authors_batch

Fetch multiple author profiles efficiently.

search_semantic_scholar_snippets

Search within paper text to find relevant passages.

get_semantic_scholar_paper_recommendations_from_lists

Get recommendations from multiple positive and negative examples to refine discovery.

get_semantic_scholar_paper_recommendations

Find papers similar to a target work based on shared features.