# OpenAlex Scholarly API
> Open scholarly analytics as an API, powered by OpenAlex — the open index of the world\x27s research covering over 250 million works and 90 million authors. Look up researcher profiles with their total works, citation counts, h-index, i10-index and current affiliation, fetch any author by OpenAlex id or ORCID, rank institutions (universities and labs) by research output and citations, search hundreds of millions of scholarly works complete with citation counts, open-access status, venue and author lists (sortable by citations or date), and explore the full topic taxonomy of science by domain, field and subfield. Perfect for research-intelligence and bibliometrics tools, university and grant dashboards, literature-discovery apps, science maps and citation analysis. All data is CC0 and live. No accounts, no upstream key. For DOI metadata use the Crossref API and for preprints the arXiv API.

## Authentication
All requests require your oanor API key in the `x-oanor-key` header. Get one at https://www.oanor.com/developer/keys.

```bash
curl -H "x-oanor-key: oanor_live_…" "https://api.oanor.com/openalex-api/..."
```

## Pricing
- **Free** (Free) — 3,600 calls/Mo, 2 req/s
- **Starter** ($6/Mo) — 46,000 calls/Mo, 5 req/s
- **Pro** ($16/Mo) — 224,000 calls/Mo, 15 req/s
- **Mega** ($42/Mo) — 1,110,000 calls/Mo, 40 req/s

## Endpoints

### Authors

#### `GET /v1/author` — One researcher by id/ORCID

**Parameters:**
- `id` (query, required, string) — OpenAlex id or ORCID Example: `A5108093963`

**Example:**
```bash
curl -H "x-oanor-key: $KEY" \
  "https://api.oanor.com/openalex-api/v1/author?id=A5108093963"
```

**Response:**
```json
{
    "data": {
        "author": {
            "id": "A5108093963",
            "name": "Geoffrey E. Hinton",
            "orcid": null,
            "topics": [
                "Neural Networks and Applications",
                "Generative Adversarial Networks and Image Synthesis",
                "Music and Audio Processing",
                "Domain Adaptation and Few-Shot Learning",
                "Topic Modeling"
            ],
            "h_index": 137,
            "i10_index": 304,
            "institution": "University of New Brunswick",
            "works_count": 384,
            "cited_by_count": 448228,
            "mean_citedness": 34,
            "institution_country": "CA"
        }
    },
    "meta": {
        "timestamp": "2026-06-01T00:03:53.775Z",
        "request_id": "2888b59e-5b54-4a24-a4c3-a53f7eacebfe"
    },
    "status": "ok",
    "message": "Author retrieved",
    "success": true
}
```

#### `GET /v1/authors` — Search researchers + metrics

**Parameters:**
- `search` (query, required, string) — Author name Example: `Geoffrey Hinton`
- `limit` (query, optional, string) — Max 1-50 Example: `20`
- `page` (query, optional, string) — Page Example: `1`

**Example:**
```bash
curl -H "x-oanor-key: $KEY" \
  "https://api.oanor.com/openalex-api/v1/authors?search=Geoffrey+Hinton&limit=20&page=1"
```

**Response:**
```json
{
    "data": {
        "page": 1,
        "count": 13,
        "query": "Geoffrey Hinton",
        "total": 13,
        "authors": [
            {
                "id": "A5108093963",
                "name": "Geoffrey E. Hinton",
                "orcid": null,
                "topics": [
                    "Neural Networks and Applications",
                    "Generative Adversarial Networks and Image Synthesis",
                    "Music and Audio Processing",
                    "Domain Adaptation and Few-Shot Learning",
                    "Topic Modeling"
                ],
                "h_index": 137,
                "i10_index": 304,
                "institution": "University of New Brunswick",
                "works_count": 384,
                "cited_by_count": 448228,
                "mean_citedness": 34,
                "institution_country": "CA"
            },
            {
                "id": "A5110248343",
                "name": "Geoffrey E. Hinton",
                "orcid": null,
                "topics": [
                    "Neural Networks and Applications",
                    "Speech Recognition and Synthesis",
                    "Blind Source Separation Techniques",
                    "Generative Adversarial Networks and Image Synthesis",
                    "Bayesian Modeling and Causal Inference"
                ],
                "h_index": 23,
                "i10_index": 25,
                "institution": "University of Toronto",
      
…(truncated, see openapi.json for full schema)
```

### Institutions

#### `GET /v1/institutions` — Search institutions by output

**Parameters:**
- `search` (query, required, string) — Institution name Example: `MIT`
- `limit` (query, optional, string) — Max results Example: `20`

**Example:**
```bash
curl -H "x-oanor-key: $KEY" \
  "https://api.oanor.com/openalex-api/v1/institutions?search=MIT&limit=20"
```

**Response:**
```json
{
    "data": {
        "page": 1,
        "count": 20,
        "query": "MIT",
        "total": 39,
        "institutions": [
            {
                "id": "I63966007",
                "ror": "https://ror.org/042nb2s44",
                "city": "Cambridge",
                "name": "Massachusetts Institute of Technology",
                "type": "education",
                "country": "US",
                "h_index": 2267,
                "homepage": "https://web.mit.edu",
                "works_count": 342877,
                "cited_by_count": 63292997
            },
            {
                "id": "I4210110987",
                "ror": "https://ror.org/01wp8zh54",
                "city": "Cambridge",
                "name": "IIT@MIT",
                "type": "facility",
                "country": "US",
                "h_index": 534,
                "homepage": "https://www.iit.it/research/lines/iit-mit",
                "works_count": 17676,
                "cited_by_count": 1817471
            },
            {
                "id": "I4210122954",
                "ror": "https://ror.org/022z6jk58",
                "city": "Lexington",
                "name": "MIT Lincoln Laboratory",
                "type": "facility",
                "country": "US",
                "h_index": 407,
                "homepage": "https://www.ll.mit.edu/",
                "works_count": 15910,
                "cited_by_count": 1313341
            },
            {
                "id"
…(truncated, see openapi.json for full schema)
```

### Works

#### `GET /v1/works` — Search scholarly works

**Parameters:**
- `search` (query, required, string) — Title/keywords Example: `attention is all you need`
- `sort` (query, optional, string) — citations|date Example: `citations`
- `limit` (query, optional, string) — Max 1-50 Example: `20`
- `page` (query, optional, string) — Page Example: `1`

**Example:**
```bash
curl -H "x-oanor-key: $KEY" \
  "https://api.oanor.com/openalex-api/v1/works?search=attention+is+all+you+need&sort=citations&limit=20&page=1"
```

**Response:**
```json
{
    "data": {
        "page": 1,
        "count": 20,
        "query": "attention is all you need",
        "total": 2428770,
        "works": [
            {
                "id": "W4385245566",
                "doi": "https://doi.org/10.4230/lipics.itp.2023.19",
                "type": "preprint",
                "year": 2023,
                "title": "MizAR 60 for Mizar 50",
                "venue": "DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)",
                "topics": [
                    "Natural Language Processing Techniques",
                    "Topic Modeling",
                    "Multimodal Machine Learning Applications"
                ],
                "authors": [
                    "Jakubův, Jan",
                    "Chvalovský, Karel",
                    "Goertzel, Zarathustra",
                    "Kaliszyk, Cezary",
                    "Olšák, Mirek",
                    "Piotrowski, Bartosz",
                    "Schulz, Stephan",
                    "Suda, Martin",
                    "Urban, Josef"
                ],
                "open_access": {
                    "is_oa": true,
                    "status": "green"
                },
                "cited_by_count": 75911,
                "references_count": 0
            },
            {
                "id": "W2896457183",
                "doi": "https://doi.org/10.4230/lipics.cosit.2022.18",
                "type": "preprint",
                "year": 2018,
         
…(truncated, see openapi.json for full schema)
```

### Topics

#### `GET /v1/topics` — Search science topics

**Parameters:**
- `search` (query, required, string) — Topic Example: `machine learning`
- `limit` (query, optional, string) — Max results Example: `20`

**Example:**
```bash
curl -H "x-oanor-key: $KEY" \
  "https://api.oanor.com/openalex-api/v1/topics?search=machine+learning&limit=20"
```

**Response:**
```json
{
    "data": {
        "page": 1,
        "count": 20,
        "query": "machine learning",
        "total": 118,
        "topics": [
            {
                "id": "T11948",
                "name": "Machine Learning in Materials Science",
                "field": "Materials Science",
                "domain": "Physical Sciences",
                "subfield": "Materials Chemistry",
                "description": "This cluster of papers focuses on the application of materials informatics, machine learning, and high-throughput computational techniques to accelerate materials innovation. It encompasses topics such as property predictions, crystal structures, molecular dynamics, and data mining in the context of materials science and engineering.",
                "works_count": 138533,
                "cited_by_count": 1017249
            },
            {
                "id": "T12254",
                "name": "Machine Learning in Bioinformatics",
                "field": "Biochemistry, Genetics and Molecular Biology",
                "domain": "Life Sciences",
                "subfield": "Molecular Biology",
                "description": "This cluster of papers focuses on the prediction of protein subcellular localization using various computational methods such as amino acid composition, machine learning algorithms like support vector machines, and the analysis of signal peptides and transmembrane topology. The research aims to improve the accuracy and reliability of pre
…(truncated, see openapi.json for full schema)
```

### Meta

#### `GET /v1/meta` — Usage notes

**Example:**
```bash
curl -H "x-oanor-key: $KEY" \
  "https://api.oanor.com/openalex-api/v1/meta"
```

**Response:**
```json
{
    "data": {
        "note": "Open scholarly analytics. /v1/authors?search=Geoffrey Hinton = researcher profiles with works count, total citations, h-index, i10-index & affiliation; /v1/author?id=A5023888391 (or an ORCID) = one researcher in full; /v1/institutions?search=MIT = universities & labs ranked by research output and citations; /v1/works?search=attention is all you need (&sort=citations|date) = scholarly works with citation counts, open-access status, venue & authors; /v1/topics?search=machine learning = the science topic taxonomy. Covers 250M+ works, 90M+ authors. Data from OpenAlex (CC0). For DOI metadata use the Crossref API; for arXiv preprints the arXiv API.",
        "source": "OpenAlex (api.openalex.org)",
        "endpoints": [
            "/v1/authors",
            "/v1/author",
            "/v1/institutions",
            "/v1/works",
            "/v1/topics",
            "/v1/meta"
        ]
    },
    "meta": {
        "timestamp": "2026-06-01T00:04:00.326Z",
        "request_id": "fc64e4e9-6d30-431f-aea3-8c9f136a5248"
    },
    "status": "ok",
    "message": "Meta retrieved",
    "success": true
}
```


---
Marketplace page: https://www.oanor.com/api/openalex-api
OpenAPI spec: https://www.oanor.com/api/openalex-api/openapi.json