CORE API v2

Name: CORE API v2 API
Brand: CORE API v2
Availability: InStock

★ Only Publicly Available OpenAPI DocumentEducationLmsapiKey18 EndpointsREST

For Agents

Search and retrieve open access research articles, journals and repository metadata across millions of harvested papers, with full-text PDF access where available.

Quickstart

Get started with CORE API v2 in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"search CORE for open access research papers"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with CORE API v2 API.

Search articles using Elasticsearch-style queries across title, authors, full text and year

Retrieve a specific article by CORE ID and download its full-text PDF when available

Find near-duplicate articles for plagiarism detection or deduplication of search results

Look up journals by ISSN to inspect their indexed coverage in CORE

GET STARTED

Start building with CORE API v2 API

Explore with Jentic

View OpenAPI Document

Use for: Search CORE for open access papers about transformer language models, Get the full record for a CORE article by its CORE ID, Download the PDF for a specific CORE article, Find near-duplicate articles to a paper I have indexed

Not supported: Does not handle paywalled content licensing, citation export, or peer review workflows — use for open access article and repository discovery only.

Jentic publishes the only available OpenAPI document for CORE API v2, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for CORE API v2, keeping it validated and agent-ready. CORE is the world's largest aggregator of open access research, harvesting articles, journals and repositories and exposing them through a JSON API organised around three resource types. The 18 endpoints cover article retrieval by CORE ID with full-text PDF download, batch get and search, journal lookup by ISSN, repository metadata and similarity-based article discovery. Search supports an Elasticsearch-style query syntax over fields like title, authors, fullText and year, and authentication is an API key passed as a query parameter or header.

Use Cases

Patterns agents use CORE API v2 API for, with concrete tasks.

★ Open Access Literature Search for Research Tools

Reference managers and research assistants can let users search CORE's open access corpus directly and retrieve metadata plus full text. The search endpoints accept Elasticsearch-style queries (e.g. title:psychology AND year:>2022) and the get endpoints pull full article records and PDFs for citation and reading.

GET /articles/search/{query} with the query 'title:transformer AND fullText:attention AND year:>2020' and return the top ten article CORE IDs with titles.

Plagiarism and Similarity Detection

Editorial workflows and academic integrity tools can use CORE's similarity endpoint to compare submitted text against the open access corpus. POST /articles/similar takes input text and returns the most similar CORE articles, while POST /articles/dedup surfaces near-duplicate clusters useful for editorial review.

POST /articles/similar with the abstract of a submitted manuscript and return the five highest-scoring matches with their CORE IDs and titles.

Repository and Journal Coverage Auditing

Library and scholarly communication teams can audit which institutional repositories and journals are indexed in CORE by listing repositories and journal records. POST /journals/get accepts batches of ISSNs to confirm coverage, supporting open access policy reporting and discoverability checks.

POST /journals/get with a list of department ISSNs and report which are indexed in CORE plus how many articles each has.

AI Research Assistant with CORE Retrieval

An AI research agent can ground answers in open access literature by searching CORE through Jentic, fetching full text, and citing CORE IDs in its responses. Jentic isolates the API key, while the agent simply describes its query intent and consumes the JSON results into its retrieval-augmented pipeline.

Use Jentic to search CORE for 'climate adaptation small island states' filtered to year:>2023 and pull full text via /articles/get/{coreId}/download/pdf for the top three results.

Key Endpoints

18 endpoints — jentic publishes the only available openapi specification for core api v2, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

GET

/articles/get/{coreId}

Get an article by CORE ID

GET

/articles/get/{coreId}/download/pdf

Download full-text PDF by CORE ID

GET

/articles/search/{query}

Search articles with an Elasticsearch-style query

POST

/articles/search

Batch article search

POST

/articles/similar

Find articles similar to input text

POST

/articles/dedup

Get near-duplicate articles

GET

/journals/get/{issn}

Find a journal by ISSN

GET

/articles/get/{coreId}

Get an article by CORE ID

GET

/articles/get/{coreId}/download/pdf

Download full-text PDF by CORE ID

GET

/articles/search/{query}

Search articles with an Elasticsearch-style query

POST

/articles/search

Batch article search

POST

/articles/similar

Find articles similar to input text

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

The CORE API key sits in the Jentic credential vault. Agents searching, fetching or similarity-comparing articles through Jentic never hold the key directly; Jentic injects it into the query string or header at execution time.

Intent-based discovery

Agents search Jentic with intents like 'search CORE open access papers' or 'find similar CORE articles' and Jentic returns the matching /articles, /journals or /repositories operation along with its query schema and Elasticsearch-style filters.

Time to first call

Direct integration: 1-2 days to learn the Elasticsearch-style query syntax and wire up search, similarity and PDF retrieval. Through Jentic: under 30 minutes from signup to first article search.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

OpenAlex API

Open scholarly knowledge graph with works, authors, institutions and concepts

Choose OpenAlex when the agent needs author and institution graph data, not just article retrieval and full text.

Alternative

Crossref API

DOI-keyed citation metadata for the broader scholarly record

Pick Crossref when the agent needs DOI-anchored citation metadata for both open and closed access works.

Complementary

DataCite REST API

DOI metadata for research datasets, complementing CORE's article focus

Use DataCite alongside CORE when an agent needs to pair a paper with its associated datasets and supplementary materials.

FAQs

Specific to using CORE API v2 API through Jentic.

Why is there no official OpenAPI spec for CORE API v2?

CORE does not publish an OpenAPI specification at this URL. Jentic generates and maintains this spec so that AI agents and developers can call CORE API v2 via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the CORE API v2 use?

CORE uses an API key, accepted either as a query parameter or in a request header. Through Jentic the key sits in the credential vault and is attached to outbound requests at execution time.

Can I download the full-text PDF of an article through the CORE API v2?

Yes. GET /articles/get/{coreId}/download/pdf returns the full-text PDF when CORE has it harvested. Not every article has a PDF available, so check the response status before parsing the body.

How does CORE search query syntax work?

Search supports Elasticsearch-style queries over fields like title, description, fullText, authors, publisher, doi, oai, identifiers, language.name and year. Examples: title:psychology AND language.name:English, or repositoryDocument.metadataUpdated:>2024-01-01.

What rate limits apply to the CORE API v2?

The OpenAPI spec does not declare formal rate limits. Use the batch endpoints POST /articles/get and POST /journals/get for bulk lookups instead of looping single GETs, and back off on HTTP 429.

How do I find similar articles to a piece of text through Jentic with the CORE API v2?

Run pip install jentic, search Jentic with 'find similar CORE articles', load the operation schema for POST /articles/similar and execute it with the input text to receive ranked similar articles.