Summary
Wraps the OpenAlex API to give Claude access to scholarly research data without authentication. You can search academic papers, authors, institutions, and citation networks directly from your MCP client. Part of the Pipeworx gateway ecosystem, which means you can either connect to this specific server or tap into their full gateway for 250+ data sources. Includes an ask_pipeworx tool that lets you query in natural language instead of calling specific endpoints. Useful when you need to pull academic metadata, track research trends, or build literature reviews without managing API keys or rate limits yourself.
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →Tools
Public tool metadata for what this MCP can expose to an agent.
3 tools
openalex_resolve_nameResolve a name or partial name to an OpenAlex ID. Returns up to 10 matches with disambiguation hints. ALWAYS use this before filtering by entity — names are ambiguous, IDs are not. Also accepts DOIs directly for quick lookup. Response time ~200ms.3 params
Resolve a name or partial name to an OpenAlex ID. Returns up to 10 matches with disambiguation hints. ALWAYS use this before filtering by entity — names are ambiguous, IDs are not. Also accepts DOIs directly for quick lookup. Response time ~200ms.
Parameters* required
entity_typestringEntity type to search. Omit for cross-entity search (useful when entity type is unknown).one of
works · authors · sources · institutions · topics · keywordsfiltersobjectNarrow autocomplete results with filters. Example: restrict to a specific country or publication year range.
querystringName or partial name to resolve. Also accepts DOIs for quick lookup.
openalex_search_entitiesSearch, filter, sort, or retrieve by ID. Covers all OpenAlex entity types (works, authors, sources, institutions, topics, keywords, publishers, funders). Pass `id` to retrieve a single entity (free, unlimited API calls). Otherwise, use `query` and/or `filters` for discovery. S...9 params
Search, filter, sort, or retrieve by ID. Covers all OpenAlex entity types (works, authors, sources, institutions, topics, keywords, publishers, funders). Pass `id` to retrieve a single entity (free, unlimited API calls). Otherwise, use `query` and/or `filters` for discovery. S...
Parameters* required
cursorstringPagination cursor from a previous response. Pass to get the next page.
entity_typestringType of scholarly entity to search.one of
works · authors · sources · institutions · topics · keywordsfiltersobjectFilter criteria as field:value pairs. AND across fields (multiple keys). OR within field: pipe-separate ("us|gb"). NOT: prefix "!" ("!us"). Range: "2020-2024". Comparison: ">100", "<50". AND within...
idstringRetrieve a single entity by ID. Supports: OpenAlex ID ("W2741809807"), DOI ("10.1038/nature12373"), ORCID ("0000-0002-1825-0097"), ROR ("https://ror.org/00hx57361"), PMID ("12345678"), PMCID ("PMC1...
per_pageintegerResults per page (1-100). Default 25.default: 25
querystringText search query. Supports boolean operators (AND, OR, NOT), quoted phrases ("exact match"), wildcards (machin*), fuzzy matching (machin~1), and proximity ("climate change"~5). Omit for filter-onl...
search_modestringSearch strategy. "keyword": stemmed full-text (default). "exact": no stemming, matches individual words (use quoted phrases for multi-word exact match). "semantic": AI embedding similarity (max 50...one of
keyword · exact · semanticdefault: keywordselectarrayOpenAlex top-level field names to return. Searches apply a curated default per entity type; pass to override. Single-entity lookups (by `id`) return the full record unless set. Invalid field names...
sortstringSort field. Prefix with "-" for descending. Common: "cited_by_count", "-publication_date", "relevance_score" (default when query present).
openalex_analyze_trendsAggregate OpenAlex entities into groups and count them. Use for trend analysis (group works by publication_year), distribution analysis (group by oa_status, type, country), and comparative analysis (group by institution or topic). Combine with filters to scope the analysis. Re...5 params
Aggregate OpenAlex entities into groups and count them. Use for trend analysis (group works by publication_year), distribution analysis (group by oa_status, type, country), and comparative analysis (group by institution or topic). Combine with filters to scope the analysis. Re...
Parameters* required
cursorstringPagination cursor from a previous response. Group-by returns max 200 groups per page. Pass cursor to get the next page. Note: paginated groups are sorted by key, not by count.
entity_typestringEntity type to aggregate.one of
works · authors · sources · institutions · topics · keywordsfiltersobjectFilter criteria (same syntax as openalex_search_entities filters). Narrows the population before aggregation. Example: group works by year, filtered to a specific topic.
group_bystringField to group by. Works examples: "publication_year", "type", "oa_status", "primary_topic.field.id", "authorships.institutions.country_code", "is_retracted". Authors: "last_known_institutions.coun...
include_unknownbooleanInclude a group for entities with no value for the grouped field. Hidden by default.default: false
OpenAlex — Open Catalog of Scholarly Works
OpenAlex is a free, open replacement for Microsoft Academic Graph (which shut down in 2022). 240M+ scholarly works with structured data on authors, institutions, concepts, citations, and venues. Open-source data model, generous API. Free, no auth (polite User-Agent + email recommended).
Part of Pipeworx — an MCP gateway connecting AI agents to 1476+ live data sources.
Why this matters for AI agents
Where Semantic Scholar is search-focused and Crossref is DOI-focused, OpenAlex is the most comprehensive structured graph: papers + authors + institutions + funders + concepts, all linked. For institutional analysis, citation networks, or systematic literature review, OpenAlex covers ground the others don't.
Common flows:
- Work lookup. Find a paper by DOI, title, or OpenAlex ID; get full structured record.
- Author / institution. Search Yale's CS department's papers in 2024.
- Concept browsing. Papers tagged with "transformer architecture" or "CRISPR Cas9."
- Citation graph. "Who cites paper X?" or "What does paper X cite?"
Citable URI: pipeworx://openalex/work/{work_id}.
Auth
Free, public. OpenAlex strongly encourages identifying yourself via mailto= query parameter or User-Agent for "polite pool" priority. Pipeworx forwards mailto=support@pipeworx.io and User-Agent: Pipeworx (mailto:support@pipeworx.io) automatically.
Entity types
OpenAlex models 5 entity types, each with stable IDs:
| Entity | ID prefix | Example |
|---|---|---|
| Work (paper) | W | W2741809807 |
| Author | A | A1234567890 |
| Institution | I | I97018004 (Yale) |
| Venue (journal/conference) | V | V202381698 |
| Concept (subject taxonomy) | C | C41008148 (computer science) |
Works are linked to authors, institutions (where authors are affiliated), venues (where they were published), and concepts (what they're about). Cross-entity queries are powerful.
Common pitfalls
- Author disambiguation. OpenAlex makes a serious effort but isn't perfect. The same person may have separate Author IDs across early-career vs late-career; common-name authors split across entities. Cross-reference with ORCID where available.
- Concept hierarchy depth. OpenAlex concepts form a 6-level tree. "Computer science" level 0 is too coarse for most queries; level 3-4 ("transformer model", "BERT model") is more useful.
- Open access status. OpenAlex tracks
oa_status(gold, green, hybrid, bronze, closed). Use it to surface free-to-read versions in your output. - Citation count vs. cited-by. OpenAlex computes citation counts from its own corpus. Same paper can show different counts in Google Scholar (broader) and Web of Science (narrower).
- Lag. New papers appear within weeks. Citations to those papers take longer because citing papers must themselves be indexed.
- Tied to Semantic Scholar? OpenAlex and Semantic Scholar are separate projects with separate data. Some overlap in coverage; some divergence in metadata. Use both for comprehensive lookups.
Quick Start
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"openalex": {
"url": "https://gateway.pipeworx.io/openalex/mcp"
}
}
}
What this endpoint actually serves
tools/list at https://gateway.pipeworx.io/openalex/mcp returns the tools in the table
above plus the shared Pipeworx meta-tools — ask_pipeworx,
discover_tools, search_within, remember/recall and the rest of the
gateway-wide set. So the tool count you see is larger than this table: a
single-pack endpoint currently lists roughly 30 shared tools alongside the
pack's own. The connection's initialize response states its exact scope, and
is the authoritative answer for a given day.
This is deliberate, not multiplexing by accident. The meta-tools are what let a
scoped connection answer a question this pack does not cover — via
ask_pipeworx, which routes across the whole catalog — without you adding a
second MCP server. There is currently no way to mount a pack endpoint without
them; if the extra schemas cost you more context than the routing is worth,
connect to the full gateway once rather than to several pack endpoints.
Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}
Both URLs reach the same gateway and the same 1476+ data sources. The
only difference is which pack's tools are listed directly; ask_pipeworx
reaches all of them from either one.
Using with ask_pipeworx
Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:
ask_pipeworx({ question: "your question about Openalex data" })
The gateway picks the right tool and fills the arguments automatically.
More
License
MIT
Featured
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →