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

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Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Stanford Semantic Scholar through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.

Ask AI about this MCP Server for Mastra AI

The Stanford Semantic Scholar MCP Server for Mastra AI 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 { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";

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

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "Stanford Semantic Scholar Agent",
    instructions:
      "You help users interact with Stanford Semantic Scholar " +
      "using 16 tools.",
    model: openai("gpt-4o"),
    tools,
  });

  const result = await agent.generate(
    "What can I do with Stanford Semantic Scholar?"
  );
  console.log(result.text);
}

main();
Stanford Semantic Scholar
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* 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 Stanford Semantic Scholar MCP Server

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

Mastra's agent abstraction provides a clean separation between LLM logic and Stanford Semantic Scholar tool infrastructure. Connect 16 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.

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 Mastra AI 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 Mastra AI

When Mastra AI 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 Mastra AI via MCP

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

01

Install dependencies

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

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

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

Explore tools

Mastra discovers 16 tools from Stanford Semantic Scholar via MCP

Why Use Mastra AI with the Stanford Semantic Scholar MCP Server

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

01

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Stanford Semantic Scholar without touching business code

02

Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation

03

TypeScript-native: full type inference for every Stanford Semantic Scholar tool response with IDE autocomplete and compile-time checks

04

One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure

Stanford Semantic Scholar + Mastra AI Use Cases

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

01

Automated workflows: build multi-step agents that query Stanford Semantic Scholar, process results, and trigger downstream actions in a typed pipeline

02

SaaS integrations: embed Stanford Semantic Scholar as a first-class tool in your product's AI features with Mastra's clean agent API

03

Background jobs: schedule Mastra agents to query Stanford Semantic Scholar on a cron and store results in your database automatically

04

Multi-agent systems: create specialist agents that collaborate using Stanford Semantic Scholar tools alongside other MCP servers

Example Prompts for Stanford Semantic Scholar in Mastra AI

Ready-to-use prompts you can give your Mastra AI 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 Mastra AI

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

01

createMCPClient not exported

Install: npm install @mastra/mcp

Stanford Semantic Scholar + Mastra AI FAQ

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

01

How does Mastra AI connect to MCP servers?

Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
02

Can Mastra agents use tools from multiple servers?

Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
03

Does Mastra support workflow orchestration?

Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.

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