Stanford Semantic Scholar MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 16 tools to Batch Get Authors, Batch Get Papers, Bulk Search Papers, and more

Name: Stanford Semantic Scholar
Price: 29 USD
Availability: InStock
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Author: Vinkius

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The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Stanford Semantic Scholar through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

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The Stanford Semantic Scholar MCP Server for OpenAI Agents SDK is a standout in the Education category — giving your AI agent 16 tools to work with, ready to go from day one.

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python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Stanford Semantic Scholar Assistant",
            instructions=(
                "You help users interact with Stanford Semantic Scholar. "
                "You have access to 16 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Stanford Semantic Scholar"
        )
        print(result.final_output)

asyncio.run(main())

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About Stanford Semantic Scholar MCP Server

Connect to the Semantic Scholar Academic Graph API and unlock the world's largest free academic knowledge graph.

The OpenAI Agents SDK auto-discovers all 16 tools from Stanford Semantic Scholar through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Stanford Semantic Scholar, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

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

The Stanford Semantic Scholar MCP Server exposes 16 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 16 Stanford Semantic Scholar tools available for OpenAI Agents SDK

When OpenAI Agents SDK connects to Stanford Semantic Scholar through Vinkius, your AI agent gets direct access to every tool listed below — spanning semantic-scholar, academic-papers, citations, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

batch

Batch 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

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

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

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

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

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

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

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

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

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

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

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

Connect Stanford Semantic Scholar to OpenAI Agents SDK via MCP

Follow these steps to wire Stanford Semantic Scholar into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 16 tools from Stanford Semantic Scholar

Why Use OpenAI Agents SDK with the Stanford Semantic Scholar MCP Server

OpenAI Agents SDK provides unique advantages when paired with Stanford Semantic Scholar through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Stanford Semantic Scholar + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Stanford Semantic Scholar MCP Server delivers measurable value.

Automated workflows: build agents that query Stanford Semantic Scholar, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Stanford Semantic Scholar, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Stanford Semantic Scholar tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Stanford Semantic Scholar to resolve tickets, look up records, and update statuses without human intervention

Example Prompts for Stanford Semantic Scholar in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Stanford Semantic Scholar immediately.

"Find the most cited papers on transformer architectures published since 2020"

"What is Geoffrey Hinton's h-index and how many papers has he published?"

"Recommend papers similar to "Attention Is All You Need""

Troubleshooting Stanford Semantic Scholar MCP Server with OpenAI Agents SDK

Common issues when connecting Stanford Semantic Scholar to OpenAI Agents SDK through Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Stanford Semantic Scholar + OpenAI Agents SDK FAQ

Common questions about integrating Stanford Semantic Scholar MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.