alperenkocyigit/semantic-scholar-graph-api
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A comprehensive Model Context Protocol (MCP) server for seamless integration with Semantic Scholar's academic database.
The Semantic Scholar MCP Server is a robust platform designed to facilitate the integration of AI assistants with Semantic Scholar's extensive academic database. This server provides a streamlined interface for accessing millions of research papers, making it an invaluable tool for researchers, academics, and AI developers. By leveraging the power of the Model Context Protocol, the server enables advanced paper discovery, AI-powered recommendations, author research, citation analysis, and content discovery. It supports natural language queries, bulk operations, and personalized paper suggestions, enhancing the efficiency and effectiveness of academic research. The server is built on Python 3.10+ and requires dependencies such as `requests`, `mcp`, and `bs4`. It offers both one-click installation options via Smithery and manual setup instructions, ensuring ease of use across various platforms.
Features
- Advanced Paper Discovery: Enables smart search, bulk operations, and precise matching for efficient literature exploration.
- AI-Powered Recommendations: Provides personalized paper suggestions and relevance scoring based on user interests.
- Author Research: Offers comprehensive author profiles and metrics, facilitating researcher identification and analysis.
- Citation Analysis: Allows exploration of citation networks, reference mapping, and access to impact metrics.
- Content Discovery: Supports text snippet searches and contextual results for in-depth content exploration.
Usages
usage with Claude Desktop macOS Linux
{ "mcpServers": { "semanticscholar": { "command": "python", "args": ["/path/to/your/semantic_scholar_server.py"] } } }
usage with Claude Desktop Windows
{ "mcpServers": { "semanticscholar": { "command": "C:\\Users\\YOUR_USERNAME\\miniconda3\\envs\\mcp_server\\python.exe", "args": ["D:\\path\\to\\your\\semantic_scholar_server.py"], "env": {}, "disabled": false, "autoApprove": [] } } }
usage with Cline
{ "mcpServers": { "semanticscholar": { "command": "bash", "args": [ "-c", "source /path/to/your/.venv/bin/activate && python /path/to/your/semantic_scholar_server.py" ], "env": {}, "disabled": false, "autoApprove": [] } } }
usage with Remote Auto Configuration
bash npx -y @smithery/cli@latest install @alperenkocyigit/semantic-scholar-graph-api --client <valid-client-name> --key <your-smithery-api-key>
usage with Remote Json Configuration macOS Linux
{ "mcpServers": { "semantic-scholar-graph-api": { "command": "npx", "args": [ "-y", "@smithery/cli@latest", "run", "@alperenkocyigit/semantic-scholar-graph-api", "--key", "your-smithery-api-key" ] } } }
usage with Remote Json Configuration Windows
{ "mcpServers": { "semantic-scholar-graph-api": { "command": "cmd", "args": [ "/c", "npx", "-y", "@smithery/cli@latest", "run", "@alperenkocyigit/semantic-scholar-graph-api", "--key", "your-smithery-api-key" ] } } }
usage with Remote Json Configuration WSL
{ "mcpServers": { "semantic-scholar-graph-api": { "command": "wsl", "args": [ "npx", "-y", "@smithery/cli@latest", "run", "@alperenkocyigit/semantic-scholar-graph-api", "--key", "your-smithery-api-key" ] } } }
Tools
search_semantic_scholar
Search papers by query
search_semantic_scholar_authors
Find authors by name
get_semantic_scholar_paper_details
Get comprehensive paper info
get_semantic_scholar_author_details
Get author profiles
get_semantic_scholar_citations_and_references
Fetch citation network
get_semantic_scholar_paper_match
Find exact paper matches
get_semantic_scholar_paper_autocomplete
Get title suggestions
get_semantic_scholar_papers_batch
Bulk paper retrieval
get_semantic_scholar_authors_batch
Bulk author data
search_semantic_scholar_snippets
Search text content
get_semantic_scholar_paper_recommendations_from_lists
Get recommendations from positive/negative examples
get_semantic_scholar_paper_recommendations
Get recommendations from single paper