Semantic Scholar Connector for AI agents.
16 live capabilities
Navigate academic research and citation graphs to find relevant literature.
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Why people use Semantic Scholar
Stanford Semantic Scholar for Academic Literature Reviews
This Connector lets your agent do the heavy lifting for you. You can ask it to find all papers in a specific field, pull their citation counts, and organize them into a list. You get a structured overview of the research landscape without the tab fatigue.
What Vinkius changes
You get a direct, conversational interface to the world's largest academic knowledge graph.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Literature Review
A PhD student asks for papers on transformer architectures from 2020 to 2024, and the agent pulls a sorted list using search_papers.
- Real-world use case 02
Impact Analysis
A data scientist wants to see how many times a specific Nature paper has been cited in the last 5 years using get_paper_citations.
- Real-world use case 03
Author Scouting
An R&D lead wants to find the top 10 authors in Quantum Computing and see their primary affiliations using search_authors.
Complete set · 16capabilities
The complete Semantic Scholar capability set.
These are the exact actions your AI can choose when you ask it to work with Semantic Scholar.
01—04
4 capabilities in this set.
Part of 16 available through Semantic Scholar.
- 01 Capability
Batch get authors
Pull multiple author profiles in one request for easier collaboration analysis. This saves time when comparing several researchers.
- 02 Capability
Get author papers
List all publications by a specific author including venue and year. Use this to review a researcher's body of work.
- 03 Capability
Get paper
Pull full metadata, abstracts, and PDF URLs using DOIs, ArXiv IDs, or PubMed IDs. It handles multiple ID formats.
- 04 Capability
Search authors
Search the academic graph to find researchers by name and see their metrics. Use this to find top contributors in a field.
05—08
4 capabilities in this set.
Part of 16 available through Semantic Scholar.
- 05 Capability
Batch get papers
Fetch multiple papers at once using various ID formats like DOI or ArXiv ID. This is perfect for building reading lists quickly.
- 06 Capability
Bulk search papers
Retrieve large sets of papers using continuation tokens for systematic reviews. This is ideal for handling large result sets.
- 07 Capability
Get author
Get a researcher's h-index, citation count, and affiliation details. It provides a clear view of academic impact.
- 08 Capability
Get multi recommendations
Find papers similar to a positive set but different from a negative set. This helps with focused literature discovery.
09—12
4 capabilities in this set.
Part of 16 available through Semantic Scholar.
- 09 Capability
Get paper authors
Identify the authors of a specific paper along with their individual h-indexes. This is useful for mapping collaboration networks.
- 10 Capability
Get paper citations
Find every paper that has cited a specific work to track its impact. It returns titles, venues, and years.
- 11 Capability
Get paper references
See the foundational papers a specific work referenced during its development. This helps trace the intellectual lineage of a study.
- 12 Capability
Get recommendations
Get AI-driven suggestions for papers similar to a single seed paper. It analyzes citation patterns and content similarity.
13—16
4 capabilities in this set.
Part of 16 available through Semantic Scholar.
- 13 Capability
Match paper title
Use fuzzy matching to find the correct paper metadata from a slightly messy title string. This resolves issues with old reference lists.
- 14 Capability
Search by field
Filter paper searches by specific fields like Medicine, Physics, or Computer Science. It covers over 20 different fields.
- 15 Capability
Search by venue
Narrow your search to specific journals like Nature or conferences like NeurIPS. This tracks publications in top-tier venues.
- 16 Capability
Search papers
Search 200M+ papers by keyword with filters for year, venue, and open access. It provides a broad overview of academic content.
Set up in minutes
One URL. Then ask Semantic Scholar to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Semantic Scholar from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_AZJpPbxBFEPF3qqoPfdyST9yhfXQRp6VrfLZlw40/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Semantic Scholar, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Semantic Scholar for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_AZJpPbxBFEPF3qqoPfdyST9yhfXQRp6VrfLZlw40/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Semantic Scholar URL.
- Step 03
Save and start
Save the connection and enable Semantic Scholar in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"stanford-semantic-scholar": {
"url": "https://edge.vinkius.com/vk_preview_AZJpPbxBFEPF3qqoPfdyST9yhfXQRp6VrfLZlw40/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Semantic Scholar
Open Agent mode in chat and ask: "Using Semantic Scholar, help me...". 16 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"stanford-semantic-scholar": {
"url": "https://edge.vinkius.com/vk_preview_AZJpPbxBFEPF3qqoPfdyST9yhfXQRp6VrfLZlw40/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Semantic Scholar
Ask Copilot: "Using Semantic Scholar, help me...". 16 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"stanford-semantic-scholar": {
"url": "https://edge.vinkius.com/vk_preview_AZJpPbxBFEPF3qqoPfdyST9yhfXQRp6VrfLZlw40/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Semantic Scholar
Open Cascade and ask: "Using Semantic Scholar, help me...". 16 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"stanford-semantic-scholar": {
"url": "https://edge.vinkius.com/vk_preview_AZJpPbxBFEPF3qqoPfdyST9yhfXQRp6VrfLZlw40/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Semantic Scholar
Ask Cline: "Using Semantic Scholar, help me...". 16 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add stanford-semantic-scholar --transport http "https://edge.vinkius.com/vk_preview_AZJpPbxBFEPF3qqoPfdyST9yhfXQRp6VrfLZlw40/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Semantic Scholar
Ask Claude: "Using Semantic Scholar, show me...". 16 tools are ready
Where the request belongs
Work Semantic Scholar can move forward.
This is for the academic who's tired of manual literature reviews or the data scientist trying to build a publication analytics dashboard.
PhD Student
Navigates the academic graph to find foundational papers for a thesis on a Tuesday afternoon.
Research Lead
Monitors specific journals and conferences for the latest R&D publications in their domain.
Data Scientist
Builds bibliometric analyses and tracks researcher impact metrics for publication reports.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsOpenAlex
Access 250M+ scholarly works with open bibliometric data. search papers, authors, institutions, and trending research topics. The open-source alternative to Scopus and Web of Science.
MIT DBLP
Search millions of computer science publications, find author profiles, and explore academic citation networks across conferences.
Scopus
Access the world's largest abstract and citation database. Search for research papers, authors, and institutional profiles directly.
Semantic Scholar
Search 200M+ academic papers with AI-powered TLDR summaries, influential citation tracking, and researcher profiles from the Allen Institute for AI.
CrossRef
Search 140M+ scholarly works across all scientific disciplines. with DOI resolution, citation counts, author lookup, and full bibliographic metadata from the world's largest DOI registry.
Stanford OpenAlex
Explore the global research landscape with open access to scholarly works, authors, institutions, and citation graphs.
Bring your own AI
Change the model, client or framework. Keep Semantic Scholar connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Semantic Scholar.
The practical details behind the request, access and result.
Can Stanford Semantic Scholar MCP find papers from specific journals?
Yes, it can filter results by specific venues like Nature, Science, or top-tier conferences like NeurIPS and CVPR.
Does the Stanford Semantic Scholar MCP require an API key?
No, this Connector uses a public API, so you can start searching immediately without setting up your own credentials.
Can I use Stanford Semantic Scholar MCP to find author h-indexes?
Yes, it pulls core metrics including h-index, total citations, and paper counts for researchers across the academic graph.
How does Stanford Semantic Scholar MCP handle large searches?
It supports bulk search operations with continuation tokens, which is perfect for systematic reviews where you need to see more than just the top few results.
Can Stanford Semantic Scholar MCP recommend new research?
Yes, it uses an AI-powered recommendation engine to suggest papers that are similar to your seed papers based on citation networks.
Does Stanford Semantic Scholar MCP support DOIs and ArXiv IDs?
Yes, you can retrieve full paper details using DOIs, ArXiv IDs, PubMed IDs, or Semantic Scholar IDs.
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.
One connection away
Give your agent a direct line to Semantic Scholar.
Connect Semantic Scholar once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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