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Stanford OpenAlex MCP Server

Bring Openalex
to Mastra AI

Learn how to connect Stanford OpenAlex to Mastra AI and start using 16 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

MCP Inspector GDPR Free for Subscribers
Get AuthorGet Author WorksGet ConceptGet FunderGet InstitutionGet SourceGet WorkSearch AuthorsSearch ConceptsSearch FundersSearch InstitutionsSearch Open AccessSearch PublishersSearch SourcesSearch TopicsSearch Works

Compatible with every major AI agent and IDE

ClaudeClaude
ChatGPTChatGPT
CursorCursor
GeminiGemini
WindsurfWindsurf
VS CodeVS Code
JetBrainsJetBrains
VercelVercel
+ other MCP clients
Stanford OpenAlex

What is the Stanford OpenAlex MCP Server?

Connect to the OpenAlex API — the fully open catalog of the global research system.

What you can do

  • Works — Search and analyze 250M+ academic works (papers, books, datasets, patents)
  • Authors — Browse 90M+ researcher profiles with h-index, i10-index, and citation metrics
  • Institutions — Explore 100K+ universities, labs, and research organizations worldwide
  • Sources — Query 240K+ journals, conferences, and repositories with impact metrics
  • Concepts — Navigate the 65K+ scientific concept taxonomy from broad to specific
  • Funders — Discover which organizations fund specific research areas
  • Publishers — Analyze the academic publishing landscape
  • Topics — Explore hierarchical topic classifications across all of science
  • Open Access — Find freely available research papers

How it works

  1. Subscribe to this server
  2. No API key required — OpenAlex is 100% free and open
  3. Start exploring the academic world from Claude, Cursor, or any MCP-compatible client

Who is this for?

  • Research Administrators — benchmark institutions, track funding landscapes
  • Bibliometricians — analyze publication trends, citation patterns, and research impact
  • Science Policy Makers — understand research funding and output by country and institution
  • Academic Librarians — explore journal metrics and open access availability

Built-in capabilities (16)

get_author

Returns name, affiliations, paper count, citation count, h-index, i10-index, 2-year mean citedness, top research concepts, and publication trends by year. The definitive tool for assessing academic impact. Get author profile with h-index, citations, and impact metrics

get_author_works

Returns works with titles, DOIs, years, citation counts, open access status, and primary venues. Sort by "cited_by_count:desc" for most cited or "publication_date:desc" for most recent. Get all works by a specific author

get_concept

Essential for understanding the structure of a research field. Get concept details with ancestors, related concepts, and trends

get_funder

Use this to understand which organizations fund specific research areas. Get funder details and funded research statistics

get_institution

Get institution details with research metrics and collaborations

get_source

Essential for evaluating journal quality and coverage. Get journal or conference details with impact metrics

get_work

Accepts OpenAlex IDs (e.g. "W2741809807"), DOIs (e.g. "https://doi.org/10.1038/s41586-021-03819-2"), PubMed IDs (e.g. "pmid:34845388"), or MAG IDs. Returns title, abstract, authors with institutions, concepts, citation count, open access status, and publication details. Get academic work details by OpenAlex ID, DOI, or PubMed ID

search_authors

Returns display name, ORCID, works count, citation count, h-index, i10-index, and last known institution. Filter examples: "cited_by_count:>10000", "works_count:>100", "last_known_institutions.country_code:US". Search 90M+ academic authors by name

search_concepts

Returns names, levels, descriptions, works counts, and citation counts. Search 65K+ scientific concepts in the knowledge hierarchy

search_funders

Returns names, countries, grants counts, works funded, and citation impact. Essential for understanding research funding landscapes. Search funding organizations worldwide

search_institutions

Returns names, countries, types, works counts, citation counts, and homepages. Filter examples: "country_code:US", "type:education", "cited_by_count:>1000000". Search 100K+ research institutions worldwide

search_open_access

This is a specialized filter of the works endpoint that returns only papers with open access PDFs. Ideal for researchers who need freely accessible literature for reading, citation, or meta-analysis. Search only open access academic works

search_publishers

Returns names, countries, works counts, and citation counts. Useful for analyzing the publishing landscape. Search academic publishers

search_sources

Returns names, ISSNs, types, works counts, citation counts, and open access status. Filter examples: "type:journal", "is_oa:true", "cited_by_count:>100000". Search 240K+ academic journals, conferences, and repositories

search_topics

Returns topic names, descriptions, associated works and citations, plus the parent field and domain. Use this to map the landscape of a research area. Search topic classifications across all of science

search_works

Supports full-text search plus structured filters. Filter syntax examples: "publication_year:2024", "open_access.is_oa:true", "type:journal-article", "cited_by_count:>100". Sort options: "cited_by_count:desc", "publication_date:desc", "relevance_score:desc". Search 250M+ academic works by keyword or filter

Why Mastra AI?

Mastra's agent abstraction provides a clean separation between LLM logic and Stanford OpenAlex 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.

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

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

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

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

M
See it in action

Stanford OpenAlex in Mastra AI

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Why Vinkius

Stanford OpenAlex and 4,000+ other MCP servers. One platform. One governance layer.

Teams that connect Stanford OpenAlex to Mastra AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.

4,000+MCP Servers ready
<40msCold start
60%Token savings
Raw MCP
Vinkius
Server catalogFind and host yourself4,000+ managed
InfrastructureSelf-hostedSandboxed V8 isolates
Credential handlingPlaintext in configVault + runtime injection
Data loss preventionNoneConfigurable DLP policies
Kill switchNoneGlobal instant shutdown
Financial circuit breakersNonePer-server limits + alerts
Audit trailNoneEd25519 signed logs
SIEM log streamingNoneSplunk, Datadog, Webhook
HoneytokensNoneCanary alerts on leak
Custom domainsNot applicableDNS challenge verified
GDPR complianceManual effortAutomated purge + export
Enterprise Security

Why teams choose Vinkius for Stanford OpenAlex in Mastra AI

The Stanford OpenAlex 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. All 16 tools execute in hardened sandboxes optimized for native MCP execution.

Your AI agents in Mastra AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

Stanford OpenAlex
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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

The Vinkius Advantage

How Vinkius secures Stanford OpenAlex for Mastra AI

Every tool call from Mastra AI to the Stanford OpenAlex MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start
Ed25519Signed audit chain
60%Token savings
FAQ

Frequently asked questions

01

Do I need an API key?

No. OpenAlex is 100% free and open. No registration or API key is required.

02

How is OpenAlex different from Semantic Scholar?

OpenAlex provides a broader ecosystem view with entities for institutions, journals, funders, publishers, and concepts — not just papers and authors. It is ideal for bibliometric analysis, institutional benchmarking, and understanding the structure of the research system. Semantic Scholar excels at AI-powered recommendations and citation graph navigation.

03

What replaced Microsoft Academic Graph?

OpenAlex was created as the free, open-source successor to Microsoft Academic Graph (MAG), which was discontinued in 2022. OpenAlex now contains over 250 million works and continues to grow, fully funded by grants to ensure permanent public access.

04

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.

05

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.

06

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.

07

createMCPClient not exported

Install: npm install @mastra/mcp

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