Semantic Scholar MCP Server
Access millions of academic papers from Semantic Scholar using the Model Context Protocol (MCP). Works with Claude Code, Claude Desktop, and other MCP-compatible editors.
Features
✅ 33 comprehensive tools - Search papers, analyze citations, manage research
✅ Smart AI prompts - Literature reviews and citation analysis
✅ Project & memory management - Organize your research workflow
✅ Fast & reliable - Built-in caching and error recovery
✅ Free to use - No API key required (optional for higher limits)
Installation
One command (recommended):
claude mcp add semantic-scholar -- uvx semantic-scholar-mcp
Manual setup (add to MCP settings):
{
"mcpServers": {
"semantic-scholar": {
"command": "uvx",
"args": ["semantic-scholar-mcp"]
}
}
}
With API key (for higher rate limits):
{
"mcpServers": {
"semantic-scholar": {
"command": "uvx",
"args": ["semantic-scholar-mcp"],
"env": {
"SEMANTIC_SCHOLAR_API_KEY": "your-api-key-here"
}
}
}
}
Get your free API key at: https://www.semanticscholar.org/product/api
Quick Start
Ask in natural language:
"Find recent papers on transformer architectures"
"Show me details for paper DOI 10.1038/nature14539"
"Get recommendations based on the BERT paper"
"Create a literature review on quantum computing"
"Save this review to memory as 'quantum_survey'"
What You Can Do
📄 Paper Research
- Search papers with advanced filters (year, citations, fields)
- Get full details: abstracts, authors, citations, references
- Convert PDFs to Markdown for analysis
- Find related papers with AI recommendations
👤 Author Analysis
- Search researchers by name or field
- Get author profiles with h-index and metrics
- List all publications by author
- Batch operations for multiple authors
🧠 Smart Features
- AI-powered paper recommendations
- Semantic search with SPECTER embeddings
- Citation network analysis
- Research trend identification
💾 Research Organization
- Create multiple research projects
- Save literature reviews and notes
- Manage research memories
- Switch between project contexts
📊 Datasets
- Access Semantic Scholar datasets
- Download paper/author data
- Get incremental updates
License
MIT License - see LICENSE for details.
⚠️ The
get_paper_fulltexttool uses PyMuPDF4LLM (AGPL licensed). Commercial usage may require a commercial PyMuPDF license.
Acknowledgments
- Semantic Scholar for the academic graph API
- Anthropic for the MCP specification
- The academic community for making research accessible
Built for researchers worldwide 🌍
Metadata
Release files for semantic-scholar-mcp 0.4.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| semantic_scholar_mcp-0.4.0.tar.gz | 370.0 kB | With provenance | Details for semantic_scholar_mcp-0.4.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| semantic_scholar_mcp-0.4.0-py3-none-any.whl | Python 3 | none | any | Details for semantic_scholar_mcp-0.4.0-py3-none-any.whl |
Total release size: 494.0 kB
Release files / semantic_scholar_mcp-0.4.0.tar.gz
| Download URL | semantic_scholar_mcp-0.4.0.tar.gz |
|---|---|
| Size | 370.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
43907ca1f38b4326269e40ee470d247418be5fac49c54fe14c561ddbf6a50d59
|
|
BLAKE2b-256 checksum How to use checksums |
58cdc1efcccdc784defc09667efcbed21f627e8aa57a8c36ed88f88d3ec3f5c5
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 11, 2025.
Transparency logRelease files / semantic_scholar_mcp-0.4.0-py3-none-any.whl
| Download URL | semantic_scholar_mcp-0.4.0-py3-none-any.whl |
|---|---|
| Size | 124.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
2d25ab3eea8fc5e8091a35888dd92521bb86a73e7bc089682a74af2ee3d3bfcd
|
|
BLAKE2b-256 checksum How to use checksums |
ff48d863510b59f023717e8adab2d299eb7a6c45e51dacc83bc0536a3c8cd9f4
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 11, 2025.
Transparency logSecurity for semantic-scholar-mcp 0.4.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for semantic_scholar_mcp-0.4.0.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 11, 2025.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.