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MCP server for academic paper search
Scholar Search MCP connects Claude, Cursor, and other MCP clients to Semantic Scholar and arXiv. It lets an assistant search papers in parallel, normalize and dedupe results, then fetch details, citations, references, author profiles, recommendations, and arXiv source files.
Builders who want their agent to search academic papers and pull structured research metadata.
You can do literature search and citation work from your agent instead of jumping between paper sites and APIs.
What it does
Unified paper search
Searches Semantic Scholar and arXiv together with `search_papers`, then normalizes and deduplicates results by title.
Paper detail lookup
Fetches one paper by DOI, arXiv ID, Semantic Scholar ID, or URL with `get_paper_details`.
Citation and reference graph
Returns incoming citations and outgoing references with `get_paper_citations` and `get_paper_references`.
Author lookup
Gets author profiles and papers with `get_author_info` and `get_author_papers`.
Recommendation and batch tools
Finds similar papers with `get_paper_recommendations` and batch fetches up to 500 papers with `batch_get_papers`.
ArXiv source download
Downloads and extracts arXiv source bundles with `download_arxiv_source`.
Cache and source controls
Uses built-in caching and environment flags to enable or disable Semantic Scholar and arXiv.
How to get it
- 1Run
pip install scholar-search-mcp
README
Scholar Search MCP
An MCP server for academic literature workflows in Claude, Cursor, and other MCP clients.
It combines Semantic Scholar and arXiv into one unified toolset, with fast parallel search, normalized outputs, source-aware deduplication, and practical research utilities (citations, references, author graph, recommendations, and arXiv source download).
Table of Contents
- Why this project
- Demo videos
- Install
- Quick setup (Claude Desktop / Cursor)
- Environment variables
- Tool list
- Testing with MCP Inspector
- Contributing
Why this project
Most paper tools force you to choose one source or one API style. scholar-search-mcp provides one MCP layer for literature search and graph retrieval:
- One MCP server, multiple scholarly sources
- Free-first defaults (
arXivworks without keys) - LLM-friendly outputs for downstream reasoning and agent workflows
- Practical research actions, not only search
- Unified search:
search_papersruns Semantic Scholar + arXiv in parallel and deduplicates by normalized title. - Research graph tools: details, citations, references, author profile/papers, and recommendations.
- Batch + source workflows: fetch up to 500 papers, and download/extract arXiv LaTeX sources.
- Operational controls: built-in caching plus env-based source toggles (enable/disable channels).
- Source strategy: built-in Semantic Scholar + arXiv, free-first by default (
arXivkey-free), optional API key for higher Semantic Scholar limits.
Demo videos
Agent writes a survey paper with Scholar Search MCP.
Install
pip install scholar-search-mcp
Requires Python 3.10+.
Quick setup (Claude Desktop / Cursor)
Use the same server command in both clients:
{
"mcpServers": {
"scholar-search": {
"command": "python",
"args": ["-m", "scholar_search_mcp"],
"env": {
"SCHOLAR_SEARCH_ENABLE_SEMANTIC_SCHOLAR": "true",
"SCHOLAR_SEARCH_ENABLE_ARXIV": "true"
}
}
}
}
SEMANTIC_SCHOLAR_API_KEY is optional. Add it only if you want higher Semantic Scholar rate limits:
{
"mcpServers": {
"scholar-search": {
"command": "python",
"args": ["-m", "scholar_search_mcp"],
"env": {
"SCHOLAR_SEARCH_ENABLE_SEMANTIC_SCHOLAR": "true",
"SCHOLAR_SEARCH_ENABLE_ARXIV": "true",
"SEMANTIC_SCHOLAR_API_KEY": "your-key"
}
}
}
}
Difference:
- Claude Desktop: edit local config file directly.
- Cursor: add an MCP server in Cursor settings UI (or corresponding settings JSON).
Claude Desktop config file locations:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
Environment variables
| Variable | Description |
|---|---|
SEMANTIC_SCHOLAR_API_KEY | Optional. Increases Semantic Scholar rate limits. |
SCHOLAR_SEARCH_ENABLE_SEMANTIC_SCHOLAR | true/false, default true. |
SCHOLAR_SEARCH_ENABLE_ARXIV | true/false, default true. |
SCHOLAR_SEARCH_CACHE_DIR | Optional cache directory path. |
SCHOLAR_SEARCH_CACHE_TTL_SECONDS | Cache TTL in seconds, default 86400. |
SCHOLAR_ARXIV_SOURCE_DIR | Default parent directory for extracted arXiv sources. |
Example (arXiv only):
{
"SCHOLAR_SEARCH_ENABLE_SEMANTIC_SCHOLAR": "false",
"SCHOLAR_SEARCH_ENABLE_ARXIV": "true"
}
Tool list
| Tool | Purpose |
|---|---|
search_papers | Search papers with optional limit, fields, year, venue. |
get_paper_details | Get one paper by DOI, arXiv ID, S2 ID, or URL. |
get_paper_citations | Get papers that cite a given paper. |
get_paper_references | Get references of a given paper. |
get_author_info | Get an author profile by ID. |
get_author_papers | Get papers by a given author. |
get_paper_recommendations | Get similar paper recommendations. |
batch_get_papers | Batch fetch paper details (up to 500 IDs). |
download_arxiv_source | Download and extract arXiv source bundle (tar.gz). |
Testing with MCP Inspector
npm install -g @modelcontextprotocol/inspector
mcp-inspector python -m scholar_search_mcp
Contributing
Issues and PRs are welcome: fork repo, create branch, add validation/tests, and open a PR with clear before/after behavior.
References
Files in the repo
- .github
- scholar_search_mcp
- static
- .gitignore
- LICENSE
- pyproject.toml
- README.md
- requirements.txt
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