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

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The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Stanford Semantic Scholar through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

Ask AI about this MCP Server for Vercel AI SDK

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

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

async function main() {
  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      // Your Vinkius token. get it at cloud.vinkius.com
      url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    },
  });

  try {
    const tools = await mcpClient.tools();
    const { text } = await generateText({
      model: openai("gpt-4o"),
      tools,
      prompt: "Using Stanford Semantic Scholar, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
Stanford Semantic Scholar
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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 Vercel AI SDK gives every Stanford Semantic Scholar tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 16 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.

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 Vercel AI 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 Vercel AI SDK

When Vercel AI 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

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

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

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

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 Vercel AI SDK via MCP

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

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the script

Save to agent.ts and run with npx tsx agent.ts
04

Explore tools

The SDK discovers 16 tools from Stanford Semantic Scholar and passes them to the LLM

Why Use Vercel AI SDK with the Stanford Semantic Scholar MCP Server

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

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Stanford Semantic Scholar integration everywhere

03

Built-in streaming UI primitives let you display Stanford Semantic Scholar tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

Stanford Semantic Scholar + Vercel AI SDK Use Cases

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

01

AI-powered web apps: build dashboards that query Stanford Semantic Scholar in real-time and stream results to the UI with zero loading states

02

API backends: create serverless endpoints that orchestrate Stanford Semantic Scholar tools and return structured JSON responses to any frontend

03

Chatbots with tool use: embed Stanford Semantic Scholar capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with Stanford Semantic Scholar through natural language queries

Example Prompts for Stanford Semantic Scholar in Vercel AI SDK

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

01

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

02

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

03

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

Troubleshooting Stanford Semantic Scholar MCP Server with Vercel AI SDK

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

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Stanford Semantic Scholar + Vercel AI SDK FAQ

Common questions about integrating Stanford Semantic Scholar MCP Server with Vercel AI SDK.

01

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
02

Can I use MCP tools in Edge Functions?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
03

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.

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