Bring Semantic Scholar
to Cursor
Learn how to connect Stanford Semantic Scholar to Cursor and start using 16 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Stanford Semantic Scholar MCP Server?
Connect to the Semantic Scholar Academic Graph API and unlock the world's largest free academic knowledge graph.
What you can do
- Paper Search — Full-text search across 200M+ papers with filters for year, field of study, venue, and open access
- Citation Analysis — Navigate forward citations (who cited this?) and backward references (what did this cite?)
- Author Profiles — Search and retrieve author metrics including h-index, paper count, and citation count
- Batch Operations — Retrieve multiple papers or authors in a single request for efficient analysis
- AI Recommendations — Get machine learning-powered paper recommendations from single or multiple seed papers
- Venue Filtering — Search within specific conferences (NeurIPS, ICML, CVPR) or journals (Nature, Science, Cell)
- Field Filtering — Search within specific fields: Computer Science, Medicine, Biology, Physics, and 20+ more
How it works
- Subscribe to this server
- No API key required — the API is fully public
- Start searching papers from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Researchers — conduct literature reviews, find related work, discover citation chains
- PhD Students — navigate the academic graph to position your research
- Data Scientists — build publication analytics and bibliometric analyses
- R&D Teams — monitor the latest publications in your domain
Built-in capabilities (16)
Returns names, affiliations, paper counts, citation counts, and h-indices. Useful for comparing researchers or building collaboration network analyses. Retrieve multiple author profiles in a single request
Accepts S2 IDs, DOIs, ArXiv IDs, or PubMed IDs. Useful for comparing papers, building reading lists, or analyzing a set of related works. Retrieve multiple papers in a single request
Each call returns a batch of results plus a continuation token. Pass the token in subsequent calls to get the next batch. Ideal for systematic literature reviews and meta-analyses. Bulk search for large result sets with token pagination
Returns name, affiliations, homepage, external IDs (DBLP, ORCID), total paper count, citation count, and h-index. The definitive tool for understanding a researcher's academic impact. Get author profile with h-index, citations, and metrics
Returns papers with titles, years, venues, citation counts, open access status, and fields of study. Essential for reviewing a researcher's body of work or finding specific publications by a known author. Get all papers by a specific author
The algorithm finds papers similar to the positive set but dissimilar to the negative set. Ideal for focused literature discovery. Get recommendations from multiple seed papers with positive/negative signals
Accepts multiple ID formats: Semantic Scholar ID (e.g. "649def34f8be52c8b66281af98ae884c09aef38b"), DOI (e.g. "10.1038/s41586-021-03819-2"), ArXiv ID (e.g. "arXiv:2106.09685"), PubMed ID (e.g. "PMID:34845388"), or ACL ID (e.g. "ACL:W12-3903"). Returns title, abstract, authors, venue, year, citation counts, open access PDF URL, and publication metadata. Get full paper details by ID, DOI, ArXiv ID, or PubMed ID
Useful for identifying research leaders and collaboration networks. Get authors of a specific paper with h-index and metrics
This is essential for understanding a paper's impact, finding follow-up work, and tracing how an idea has evolved. Returns citing paper metadata including titles, venues, years, and citation counts. Get papers that cite a given paper
Essential for literature reviews, understanding the intellectual lineage of a work, and finding foundational papers in a research area. Get papers referenced by a given paper
The algorithm analyzes citation patterns, co-citation networks, and content similarity to find the most relevant papers you should read next. This is the AI-native way to discover related literature. Get AI-powered paper recommendations from a seed paper
Uses fuzzy matching to handle slight variations. Returns the best matching paper with a match score. Ideal when you have a paper title from a reference list or bibliography and need to find its full metadata. Find an exact paper match from a title string
Returns author profiles with affiliations, paper counts, citation counts, and h-index. Use this to find researchers in a specific field, discover top contributors, or find collaborators. Search authors by name across the academic graph
Supported fields: Computer Science, Medicine, Biology, Chemistry, Physics, Mathematics, Engineering, Environmental Science, Economics, Business, Political Science, Sociology, Psychology, Art, History, Geography, Philosophy, Materials Science, Geology, Linguistics, Education, Agricultural and Food Sciences, Law. Search papers filtered by field of study
Use venue names like "Nature", "Science", "NeurIPS", "ICML", "CVPR", "ACL", "EMNLP", "The Lancet", "JAMA", "Cell", "Physical Review Letters". Essential for tracking publications in specific top-tier venues. Search papers filtered by conference or journal
Returns titles, venues, years, citation counts, open access status, fields of study, and authors. Supports filtering by year range (e.g. "2020-2024"), fields of study (e.g. "Computer Science"), venue (e.g. "Nature"), and open access availability. Search across 200M+ academic papers by keyword
Why Cursor?
Cursor's Agent mode turns Stanford Semantic Scholar into an in-editor superpower. Ask Cursor to generate code using live data from Stanford Semantic Scholar and it fetches, processes, and writes. all in a single agentic loop. 16 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.
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Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context
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Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards
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MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment
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VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools
Stanford Semantic Scholar in Cursor
Stanford Semantic Scholar and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Stanford Semantic Scholar to Cursor through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Stanford Semantic Scholar in Cursor
The Stanford Semantic Scholar MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 16 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Cursor only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Stanford Semantic Scholar for Cursor
Every tool call from Cursor to the Stanford Semantic Scholar MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Do I need an API key?
No. The Semantic Scholar API is fully public. An optional free API key increases rate limits from 1 to 10 requests per second.
What paper ID formats are supported?
Semantic Scholar accepts multiple ID formats: its own S2 Paper ID, DOI (e.g. "10.1038/..."), ArXiv ID (e.g. "arXiv:2106.09685"), PubMed ID (e.g. "PMID:34845388"), and ACL Anthology ID. This makes it easy to look up any paper regardless of where you found the reference.
How do the AI recommendations work?
The recommendation engine uses machine learning to analyze citation patterns, co-citation networks, and content similarity. You can provide one seed paper for basic recommendations, or multiple positive and negative seed papers for advanced filtering. This is the most sophisticated way to discover related literature.
What is Agent mode and why does it matter for MCP?
Agent mode is Cursor's autonomous execution mode where the AI can perform multi-step tasks: reading files, editing code, running terminal commands, and calling MCP tools. Without Agent mode, Cursor operates in a simpler ask-and-answer mode that doesn't support tool calling. Always ensure you're in Agent mode when working with MCP servers.
Where does Cursor store MCP configuration?
Cursor looks for MCP server configurations in a mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.
Can Cursor use MCP tools in inline edits?
No. MCP tools are only available in Agent mode through the chat panel. Inline completions and Tab suggestions do not trigger MCP tool calls. This is by design. tool calls require user visibility and approval.
How do I verify MCP tools are loaded?
Open Settings → Features → MCP and look for your server name. A green indicator means the server is connected. You can also check Agent mode's available tools by clicking the tools dropdown in the chat panel.
Tools not appearing in Cursor
Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.
Server shows as disconnected
Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.
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