Semantic Scholar MCP Server for OpenAI Agents SDK 4 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Semantic Scholar through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="Semantic Scholar Assistant",
instructions=(
"You help users interact with Semantic Scholar. "
"You have access to 4 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Semantic Scholar"
)
print(result.final_output)
asyncio.run(main())
* 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
About Semantic Scholar MCP Server
Connect your AI agent to the world's most AI-enhanced academic knowledge graph, built and maintained by the Allen Institute for AI (AI2).
The OpenAI Agents SDK auto-discovers all 4 tools from Semantic Scholar through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Semantic Scholar, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- AI-Powered Search — Find papers across 200M+ works with AI-generated TLDR summaries that distill each paper into a single sentence of key insight
- Influential Citations — Beyond simple citation count, see how many influential citations a paper has received — those that meaningfully build upon the cited work
- Multi-Format Lookup — Access papers by Semantic Scholar ID, DOI, ArXiv ID (arXiv:2106.09685), or PubMed ID (PMID:12345)
- Citation Graph — Explore the full citation chain of any paper, with TLDR summaries for each citing work
- Researcher Profiles — Find academics by name with paper counts, total citations, and h-index metrics
The Semantic Scholar MCP Server exposes 4 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Semantic Scholar to OpenAI Agents SDK via MCP
Follow these steps to integrate the Semantic Scholar MCP Server with OpenAI Agents SDK.
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 4 tools from Semantic Scholar
Why Use OpenAI Agents SDK with the Semantic Scholar MCP Server
OpenAI Agents SDK provides unique advantages when paired with 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
Semantic Scholar + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Semantic Scholar MCP Server delivers measurable value.
Automated workflows: build agents that query Semantic Scholar, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Semantic Scholar, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Semantic Scholar tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Semantic Scholar to resolve tickets, look up records, and update statuses without human intervention
Semantic Scholar MCP Tools for OpenAI Agents SDK (4)
These 4 tools become available when you connect Semantic Scholar to OpenAI Agents SDK via MCP:
get_semantic_citations
Essential for literature reviews and impact analysis. Find papers that cite a specific work on Semantic Scholar
get_semantic_paper
Accepts Semantic Scholar paper ID, DOI, ArXiv ID (e.g. arXiv:2106.09685), or PMID (e.g. PMID:12345). Get full paper details from Semantic Scholar by paper ID or DOI
search_semantic_author
Returns paper count, total citations, and h-index for each researcher. Find researchers and their publication metrics on Semantic Scholar
search_semantic_scholar
Returns papers with AI-generated TLDR summaries, citation counts, influential citation counts, and fields of study. Covers Computer Science, Medicine, Biology, Physics, and all STEM fields. Search 200M+ academic papers with AI-powered TLDR summaries and influence scores
Example Prompts for Semantic Scholar in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Semantic Scholar immediately.
"What are the most cited papers on transformer architecture in deep learning?"
"Get the full details of the LoRA paper using its ArXiv ID arXiv:2106.09685."
"Find the researcher Yann LeCun and show me his publication metrics."
Troubleshooting Semantic Scholar MCP Server with OpenAI Agents SDK
Common issues when connecting Semantic Scholar to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Semantic Scholar + OpenAI Agents SDK FAQ
Common questions about integrating Semantic Scholar MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Semantic Scholar with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
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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.
Connect Semantic Scholar to OpenAI Agents SDK
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.