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OpenAlex MCP Server: 200M Academic Papers, Authors, Institutions for AI Agents

An Apify-hosted MCP server exposing 8 tools to query OpenAlex — the open catalogue of 200M+ scholarly works, authors, institutions, sources, and concepts. HTTP-only, no API key. $0.005 per tool-call.

⭐ Bookmark this OpenAlex MCP Server — Apify ranks actors by bookmarks, so it directly helps the visibility of this actor on the Apify Store. → Bookmark it on the Apify Store

What can this OpenAlex MCP Server do?

• 📚 Search 200M+ scholarly works — papers, books, datasets across every discipline.
• 👩‍🔬 Find authors with h-index, ORCID, institution — full bibliometric profiles.
• 🏛️ Resolve institutions & ROR IDs — universities, hospitals, research orgs in 200+ countries.
• 🧠 Query the OpenAlex concept taxonomy — Wikidata-linked research topics, levels 0-5.
• 📰 Discover sources — journals, conferences, repositories, OA status, DOAJ flag.
• 🤖 MCP-shaped for AI agents — call from Claude, Cursor, Continue with one tool dispatcher.

What data can you extract with the OpenAlex MCP Server?

How to use the OpenAlex MCP Server

1. Open the actor on Apify: apify.com/dltik/mcp-server-openalex.
2. Discover the tool catalog — run once with mode=list_tools (free, no charge).
3. Pick a tool — search_works, get_work, search_authors, etc.
4. Pass arguments — e.g. {"query": "climate change", "limit": 10}.
5. Wire it into your agent — Claude / Cursor / Continue / LangChain / LlamaIndex, via Apify's MCP bridge or run-sync-get-dataset-items.

How much does the OpenAlex MCP Server cost?

PAY_PER_EVENT — $0.005 per tool-call. list_tools mode is free (discovery). Failed runs are not charged.

Per call, the OpenAlex MCP Server averages ~5 s of compute on 256 MB RAM and ~0.05 MB of bandwidth — fully covered by the per-event price.

Input parameters

Output example

{
"openalex_id":"W2741809807",
"doi":"https://doi.org/10.7717/peerj.4375",
"title":"The state of OA: a large-scale analysis of the prevalence and impact of Open Access articles",
"type":"article",
"publication_year":2018,
"publication_date":"2018-02-13",
"language":"en",
"cited_by_count":1132,
"referenced_works_count":62,
"open_access_status":"gold",
"open_access_url":"https://peerj.com/articles/4375.pdf",
"is_oa":true,
"primary_source":{
"id":"S2738156628",
"display_name":"PeerJ",
"issn_l":"2167-8359",
"type":"journal"
},
"authors":["Heather Piwowar","Jason Priem","Vincent Larivière","Juan Pablo Alperin"],
"n_authors":8,
"concepts":[
{"id":"C2779343474","display_name":"Open access","level":2,"score":0.94}
],
"abstract":"Despite growing interest in Open Access (OA) to scholarly literature ..."
}

Use cases for the OpenAlex MCP Server

• AI research assistants — let Claude or Cursor pull verifiable citations from OpenAlex during a literature review.
• Grant writing & competitive intelligence — surface the top-cited authors and institutions on a topic in seconds.
• CRM / lead-gen enrichment for academic SaaS — enrich researcher records with h-index, ORCID, last institution, country.
• Bibliometric dashboards — track OA adoption, citation counts, journal coverage across a discipline.
• Knowledge graph builders — pull OpenAlex's concept taxonomy and author–institution edges into Neo4j / RDF.
• Systematic reviews — automate PRISMA-style filtering by year, OA status, concept score.

API examples

Python (Apify client):

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("dltik/mcp-server-openalex").call(run_input={
"mode":"call_tool",
"tool_name":"search_works",
"arguments":{"query":"transformer architecture","limit":5,"sort":"cited_by_count:desc"}
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item.get("title"),"—", item.get("cited_by_count"))

curl (synchronous run):

curl-X POST "https://api.apify.com/v2/acts/dltik~mcp-server-openalex/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN"\
-H"Content-Type: application/json"\
-d'{
 "mode": "call_tool",
 "tool_name": "get_work",
 "arguments": {"doi": "10.1038/s41586-021-03819-2"}
 }'

FAQ — OpenAlex MCP Server

Why use the OpenAlex MCP Server on Apify vs hitting api.openalex.org directly? Maintenance + agent-shape. The OpenAlex MCP Server normalizes nested objects, reconstructs abstracts from OpenAlex's inverted index, exposes a tool dispatcher native to MCP, and bills per call — no rate-limit handling, no schema-drift code in your agent.

What's the polite pool and do I need to set mailto? OpenAlex serves anonymous requests with stricter limits. Passing an email via mailto puts you in the "polite pool" with ~100k req/day. The OpenAlex MCP Server injects a maintainer email by default — set your own mailto for high-volume usage.

How are abstracts returned? OpenAlex stores abstracts as an inverted index ({word: [positions]}). When reconstruct_abstract: true (default), the OpenAlex MCP Server rebuilds the plain-text abstract into the abstract field. The raw abstract_inverted_index is always kept too.

How do I paginate beyond 10,000 results? Pass cursor: "*" on the first call, then forward the next cursor returned by OpenAlex. The OpenAlex MCP Server exposes the cursor argument on search_works for exactly this.

Is there a free tier? list_tools is always free (catalog discovery). call_tool is $0.005 per call, billed only on success.

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Other scrapers by dltik

License: MIT · Author: dltik