# Semantic Scholar MCP for AI Agents AI Agent Connect

> Semantic Scholar lets you search over 200 million academic papers with your AI client. It gives you instant TLDR summaries, tracks influential citations, and pulls up researcher profiles with metrics like h-index and total citations. It's the fastest way to navigate the world's biggest academic knowledge graph without digging through endless search results.

## Overview
- **Category:** the-unthinkable
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_8zAprfIHUkrZA9BorlGo4lSh4aqrzDrrqy7KLAZz/ai-agent-connect
- **Tags:** academic-research, citation-analysis, knowledge-graph, literature-review, scientific-data, research-profiles, summarization, stem

## Description

This Connector connects your AI agent to the world's most AI-enhanced academic knowledge graph. It lets you navigate over 200 million papers by pulling in AI-generated summaries that distill each work into a single sentence of key insight. Instead of clicking through endless search results, you can ask your agent to find specific papers using DOIs, ArXiv IDs, or PubMed IDs. It even handles complex citation chains, letting you see how ideas evolve across the academic landscape. You can scout researchers by pulling up their h-index and total citation counts to see who's actually making an impact. When you add this to your Vinkius catalog, you turn a week of manual literature review into a quick conversation. It's about getting the right data points without the tab fatigue.

## Tools

### search_semantic_author
Retrieve paper counts, total citations, and h-index metrics for any researcher. Use this to scout talent or evaluate academic impact.

### search_semantic_scholar
Search 200M+ papers and get AI-generated TLDR summaries and influence scores. This helps you quickly vet papers in any STEM field.

### get_semantic_citations
Find papers that cite a specific work to help with impact analysis. This is great for building a citation graph during a literature review.

### get_semantic_paper
Get full paper details using a DOI, ArXiv ID, or PubMed ID. This lets your agent pull data directly without you having to browse a website.

## Prompt Examples

**Prompt:** 
```
What are the most cited papers on transformer architecture in deep learning?
```

**Response:** 
```
Top results include:

* **Attention Is All You Need** by Vaswani et al. (2017)
* **TLDR:** The Transformer, a new network architecture based solely on attention mechanisms, achieves superior quality on machine translation tasks.
* **Citations:** 120,000+ (25,000+ influential)
* **Fields:** Computer Science, Linguistics
```

**Prompt:** 
```
Get the full details of the LoRA paper using its ArXiv ID arXiv:2106.09685.
```

**Response:** 
```
Found: **LoRA: Low-Rank Adaptation of Large Language Models** by Edward Hu et al. (2021).

* **TLDR:** LoRA freezes the pre-trained model weights and injects trainable rank decomposition matrices, reducing trainable parameters by 10,000x and GPU memory by 3x.
* **Citations:** 8,500+ (2,100 influential)
* **Fields:** CS, Mathematics
* **Link:** arxiv.org/abs/2106.09685
```

**Prompt:** 
```
Find the researcher Yann LeCun and show me his publication metrics.
```

**Response:** 
```
Found researcher **Yann LeCun**

* **Role:** Author at Meta AI / NYU
* **Papers:** 950+
* **Total Citations:** 380,000+
* **h-index:** 162
* **Known for:** Pioneering work in convolutional neural networks, self-supervised learning, and modern AI architectures.
```

## Capabilities

### Get one-sentence TLDR summaries
Your agent pulls instant summaries for academic papers to help you assess relevance quickly.

### Identify influential citations
Distinguish between raw citation counts and the works that actually build on previous research.

### Lookup papers by unique IDs
Access specific research using DOIs, ArXiv IDs, or PubMed IDs directly through your agent.

### Map citation chains
Trace how scientific ideas evolve by exploring the full history of citations for any paper.

### Retrieve researcher metrics
Get h-index, total citations, and publication counts for academics in any field.

## Use Cases

### Mapping an evolving AI architecture
A researcher needs to see how a specific AI architecture has changed over 5 years. They ask the agent to map out the citation chain of a seminal paper to see how the technology evolved.

### Vetting niche biology research
A student is looking for the most relevant papers on a niche biology topic. They ask the agent to search the database for papers with one-sentence summaries to quickly vet the results.

### Identifying top experts in a field
An R&D lead needs to find the top experts in a new field. They ask the agent to pull up publication metrics and h-index scores for several prominent names in the industry.

### Quickly pulling data for a specific ArXiv ID
A user has a specific ArXiv ID and needs the full paper details. They ask the agent to pull the complete data for that specific ID instantly.

## Benefits

- Save hours of reading by getting one-sentence summaries for all the papers your agent finds.
- Identify high-impact research using influential citation counts instead of just raw numbers.
- Map out how ideas evolve by tracing the full citation chain of any specific work.
- Quickly verify researcher credentials by pulling up h-index and total citation counts.
- Access any paper instantly via DOI or ArXiv ID without manual searching.
- Get a structured overview of STEM fields to see what is trending now.

## How It Works

The bottom line is you get a searchable, summarized database of most major scientific papers in one place.

1. Subscribe to the Semantic Scholar MCP in the Vinkius catalog.
2. Ask your agent to find papers by topic, author, or specific ID.
3. Receive a list of results with TLDR summaries, influence scores, and citation data.

## Frequently Asked Questions

**Can Semantic Scholar help me write a literature review?**
Yes, it helps you find related papers and map out how ideas have evolved over time. This makes it much faster to organize your research.

**How does Semantic Scholar handle different paper types?**
It can look up papers using DOIs, ArXiv IDs, and PubMed IDs, making it versatile for different types of scientific archives.

**Can I find out who the most influential researchers are?**
Yes, the Connector pulls metrics like h-index and total citations for specific academics, which helps identify key figures in a field.

**Will Semantic Scholar give me a summary of the paper?**
It provides AI-generated TLDRs that distill each paper into a single sentence of key insight, so you don't have to read the full text to understand the goal.

**Is Semantic Scholar good for finding STEM research?**
Yes, it covers Computer Science, Medicine, Biology, Physics, and other major STEM fields with high-quality data.

**How do I find papers that cite a specific study?**
You can use the citation analysis tools to see the works that build on a specific paper, allowing you to see the current state of the research.

**Do I need an API key to use Semantic Scholar?**
No API key is required for basic usage. The public API provides 5,000 requests per 5 minutes shared among unauthenticated users. For higher throughput, academic and institutional users can request a free API key at semanticscholar.org, which grants dedicated rate limits of 1–10 requests per second depending on the endpoint.

**What is the TLDR feature and how does it work?**
TLDR (Too Long; Didn't Read) is an AI-generated one-sentence summary of each paper, powered by Allen AI's SciTLDR NLP model. It distills the key contribution or finding of a paper into a single, easily digestible sentence — ideal for quickly scanning relevance without reading an entire abstract or paper.

**What is the difference between total citations and influential citations?**
Total citations count every paper that references the work. Influential citations are a subset — papers where the cited work meaningfully contributes to the citing paper's research (not just a passing mention in the related work section). This metric is calculated by Semantic Scholar's AI models and provides a much more accurate measure of real scientific impact.