Integrate Stanford Semantic Scholar with Claude, Cursor, Chatbots & AI Agents MCP Server
GDPR Free for SubscribersCompatible with every major AI agent and IDE
GeminiBatch get authors on Stanford Semantic Scholar
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
Batch get papers on Stanford Semantic Scholar
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
Bulk search papers on Stanford Semantic Scholar
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
Get author on Stanford Semantic Scholar
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
Get author papers on Stanford Semantic Scholar
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
Get multi recommendations on Stanford Semantic Scholar
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
Get paper on Stanford Semantic Scholar
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
Get paper authors on Stanford Semantic Scholar
Useful for identifying research leaders and collaboration networks. Get authors of a specific paper with h-index and metrics
Get paper citations on Stanford Semantic Scholar
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
Get paper references on Stanford Semantic Scholar
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
Get recommendations on Stanford Semantic Scholar
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
Match paper title on Stanford Semantic Scholar
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
Search authors on Stanford Semantic Scholar
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
Search by field on Stanford Semantic Scholar
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
Search by venue on Stanford Semantic Scholar
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
Search papers on Stanford Semantic Scholar
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
Security & Code Integrity Audit
Every tool in the Stanford Semantic Scholar MCP Server is continuously audited by the Vinkius Security Engine. We guarantee zero-trust payload isolation, strict data boundaries, and deterministic execution for enterprise-grade AI agents.
How Vinkius protects your data
Is there a risk of the AI "going crazy" and deleting important company data?
No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.
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 does the AI access my passwords and credentials?
It simply doesn't. On Vinkius, your passwords, API keys, and login details are kept in a secure vault. The AI (like ChatGPT or Claude) merely "asks" Vinkius to perform the task. Vinkius opens the door, does the work, and hands the result back to the AI. Your credentials are never seen, read, or learned by the artificial intelligence.
What if the AI ends up reading customer data or confidential information?
We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.
Stanford Semantic Scholar Capabilities for AI Assistants
The Stanford Semantic Scholar MCP server handles authentication and payload formatting, allowing your LLM to perform deterministic actions.
Scaling semantic scholar via MCP
Integrate the Stanford Semantic Scholar server to handle semantic scholar requests natively. It provides the schemas required for ChatGPT and Cursor to manage education data.
Execute academic papers Commands with AI
The Stanford Semantic Scholar toolkit provides secure access to academic papers functions. It enables conversational agents to manage education settings deterministically.
Stanford Semantic Scholar. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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