Stanford OpenAlex MCP. Map the entire academic knowledge graph.
Stanford OpenAlex gives you open access to the global research catalog. It lets you analyze over 250 million academic works and trace connections between authors, institutions, concepts, and funding bodies worldwide. Check a researcher's full impact profile, map out scientific concept hierarchies, or find every paper funded by a specific organization.
Give Claude and any AI agent real-world access
Retrieve detailed profiles for authors, including their total citation count, h-index, i10-index, and historical publication trends.
Explore how scientific concepts relate to one another by viewing the concept hierarchy or tracing related research areas.
Determine which specific organizations fund research, allowing you to map funding sources against academic topics.
Get comprehensive details on any paper using its DOI, OpenAlex ID, or PubMed ID, including abstracts and citation information.
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What AI agents can do with Stanford OpenAlex: 16 Tools for Academic Data
Use these specific tools to query the massive catalog directly, whether you need an author's impact score or a journal's citation count.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Stanford OpenAlex MCPGet Author
Retrieves a scholar's full profile, including citation count, h-index, i10-index, and publication trends over time.
Get Author Works
Lists all papers written by a specific author, letting you sort the results by most...
Get Concept
Provides detailed information on scientific concepts, including their ancestors and...
Get Funder
Shows which organizations fund specific research areas along with statistical...
Get Institution
Gathers detailed metrics for a university or lab, including its overall research...
Get Source
Evaluates the quality of journals or conferences by retrieving their impact metrics and coverage details.
Get Work
Fetches a paper's title, abstract, authors, and citation count using its DOI, OpenAlex ID, or PubMed ID.
Search Authors
Searches the database of over 90 million authors by name and filters results based...
Search Concepts
Finds specific scientific concepts within the knowledge hierarchy, showing...
Search Funders
Searches for funding organizations worldwide, detailing their grants count, funded...
Search Institutions
Finds research institutions across the globe by name or filters them by type...
Search Open Access
Filters all available works to show only papers that have freely accessible PDFs for reading and meta-analysis.
Search Publishers
Analyzes the academic publishing market by listing major publishers, their country of origin, and citation counts.
Search Sources
Searches over 240,000 journals and conferences, providing details like ISSNs and...
Search Topics
Maps the entire landscape of science by searching topic classifications across all...
Search Works
Performs a full-text search or structured filter on 250 million works, allowing...
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Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
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Make Your AI Do More
Start with Stanford OpenAlex, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
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- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
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The Pain of Manual Academic Due Diligence
Right now, proving the impact or lineage of an idea is a nightmare. You start by Googling papers, then jump to CrossRef to get the DOI, then open a university website just to check if that author is still affiliated there, and finally, you cross-reference funding data from another dashboard. It's copy-pasting metadata across five different tabs just to build one citation graph.
With this MCP, your agent does it all in one query. You ask for the full picture—the author metrics, the linked concepts, and the primary source—and you get a single, structured data response. It's instant due diligence.
Using Stanford OpenAlex to Pinpoint Impact
The tedious steps of cross-checking publication years against institutional affiliations or manually verifying the open access status are gone. You run a search and get all that data simultaneously.
Your workflow changes from manual information retrieval to focused analysis. You stop collecting data points, and you start building arguments.
What Stanford OpenAlex MCP does for your AI
Working with modern academic research means dealing with massive datasets—millions of papers, thousands of institutions, and complex citation graphs. This MCP connects you directly to the OpenAlex API, giving your AI client deep access to this global knowledge catalog. You don't need an API key because OpenAlex is free and open.
Instead of manually hopping between Google Scholar, university websites, and journal portals, you ask your agent to do the heavy lifting. You can profile a scholar using metrics like h-index or i10-index; check which organizations are funding specific fields of study; or narrow down papers that have been published under open access licenses.
It's the power of having all the academic world’s metadata available in one place, accessible through Vinkius and your preferred AI client.
019dea60-e5a2-7074-8986-f7313b31a150 How to set up Stanford OpenAlex MCP
The bottom line is you get structured data about global research fields and people, delivered directly to your AI client for immediate analysis.
Subscribe to this MCP within Vinkius. No API key is required because the source data is openly available.
Connect your AI client (Claude, Cursor, etc.) to the catalog via the MCP connection point.
Ask your agent a specific question—like 'Show me all papers on deep learning funded by the NSF'—and it executes the necessary queries.
Who uses Stanford OpenAlex MCP
This MCP serves academic libraries, university administrators, bibliometricians, and science policy makers. It's for anyone whose job requires tracing the provenance of ideas—from funding sources back to original authors.
Checks journal details using get_source or filters search results via search_sources to determine if a required paper is open access.
Benchmarks different institutions by running searches through search_institutions and comparing citation metrics across multiple schools.
Understands the global flow of money into science using get_funder or search_funders to map which organizations are prioritizing specific research areas.
Benefits of connecting Stanford OpenAlex MCP
Pinpoint scholarly impact immediately. Instead of compiling CVs from multiple sites, use get_author to instantly gather a scholar's full citation history and h-index metrics.
Trace research funding paths. Use search_funders or get_funder to understand which organizations are investing in specific topics, helping policy makers track global science money.
Find literature easily. If you only need free papers, use search_open_access. This saves time and eliminates the frustrating step of paywall checking before citing a source.
Understand field relationships. When analyzing a niche topic, run get_concept to see its parent fields and related concepts, giving you context beyond just keywords.
Benchmark institutions accurately. Compare multiple universities' research strength by querying search_institutions, letting you compare works counts or citation metrics side-by-side.
Stanford OpenAlex MCP use cases
Assessing a Collaborator’s Standing
A PI needs to prove that a new collaborator has deep expertise in AI. They ask their agent to use search_authors with filters like 'works_count:>500' and then run get_author_works to confirm the most cited papers are all within neural network concepts.
Tracking Policy Shifts
A policy maker needs to know if climate research funding is shifting from government sources to private foundations. They use search_funders and then cross-reference the results with papers found using search_works filtered by 'climate change'.
Curating a Review Article
A librarian is writing an overview of CRISPR technology. Instead of searching journal by journal, they use get_work multiple times with different IDs and then use search_sources to ensure the journals are high-impact before adding them.
Mapping a New Field
A PhD student is exploring the boundaries of quantum computing. They ask their agent to run search_topics, which maps out the full concept hierarchy, showing related fields like particle physics and high-energy theory.
Stanford OpenAlex MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Using Google Scholar for everything
A user copies a list of 50 DOIs from one database and pastes them into another, hoping to get comprehensive metrics like h-index or concept mapping. This fails because different sites use different data models.
You must centralize your queries using get_work for individual papers, but for bulk analysis, run structured searches via search_authors and search_works. These tools consolidate the raw metadata you need.
Searching only by keywords
A user runs a keyword search on one platform and gets 20 results. They then manually try to find out which institutions are involved, requiring dozens of clicks.
Use search_works with structured filters like 'publication_year:2024' AND 'type:journal-article'. Then, use the resulting list to check institutional details via get_institution for a complete picture.
Assuming data is siloed
A researcher finds an author on one platform and assumes their work history is only visible there. They miss out on funding context.
Always run get_author first, then immediately use the resulting concepts to cross-reference with get_funder. This connects the person's output directly to who paid for it.
When to use Stanford OpenAlex MCP
Use this MCP if your core need is understanding the structure of academic knowledge—who published what, where, when, and why (funding). You need to trace connections: author to work, work to concept, or funding body to field. Don't use it if you just need a simple list of papers by title; search_works handles that. However, don't rely on this MCP for the most recent news articles, either—it tracks established scholarly literature. If your goal is purely conversational summary generation without needing structural metrics (like h-index or concept hierarchy), then a general LLM might suffice. But if you need verifiable data points—citation counts, specific concepts, funding bodies—this catalog is essential.
Frequently asked questions about Stanford OpenAlex MCP
How do I use Stanford OpenAlex for citation metrics? +
Use the get_author tool. This retrieves a scholar’s full profile, including their total citation count, h-index, and i10-index, giving you immediate impact assessment.
Can I find out who is funding a specific research topic using Stanford OpenAlex? +
Yes, use get_funder or search_funders. These tools map funding organizations to specific research areas, allowing you to trace the financial backing of science.
What is the best way to find open access papers with Stanford OpenAlex? +
The dedicated search_open_access tool filters all works and returns only those academic papers that have freely available PDFs, saving you time on paywalls.
How do I compare multiple universities' research output using Stanford OpenAlex? +
Use search_institutions to find the schools. Then, for a direct comparison of metrics across them, run get_institution on each one you want to benchmark.
Does Stanford OpenAlex cover patents or just academic papers? +
It covers works that include papers, books, datasets, and patents. Use the search_works tool with specific filters if you are looking for a particular type of output.