# Research Paper API: Search arXiv, DOI & PubMed for AI Agents (`emttn/research-papers-markdown`) Actor

arXiv API and paper search: find papers by topic, DOI, arXiv ID, PMID or PMCID and get metadata, authors and citations plus the open-license abstract and full text in markdown for AI agents where the host allows it (arXiv and PubMed are linked). Charged per paper delivered; failed lookups are free.

- **URL**: https://apify.com/emttn/research-papers-markdown.md
- **Developed by:** [Frameskim Tools](https://apify.com/emttn) (community)
- **Categories:** AI, Agents, Developer tools
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Research Papers to Markdown for AI Agents

Search academic papers by topic, or look them up by DOI, arXiv ID, PubMed ID (PMID), PubMed Central ID (PMCID) or OpenAlex ID, and get one clean item per paper with its metadata and, when its open license allows it, the abstract and full text as markdown for AI agents. Each item carries the title, authors, year, venue, citations, open access status, links, IDs and the attribution the license asks for: for literature reviews, research agents and RAG over open-access papers.

- Metadata comes from [OpenAlex](https://openalex.org) (CC0), which covers Crossref, PubMed and arXiv records.
- Abstract and full text only for papers with an open license that allows reuse: CC BY, CC BY-SA, CC BY-ND, CC0 or public domain.
- Charged per paper delivered, and once more per paper delivered with its full text; IDs that are not found are free.

More: [Research Papers to Markdown on frameskim.dev](https://frameskim.dev/research-papers-markdown)

### What you get

```json
{
  "id": "https://openalex.org/W4389519118",
  "doi": "https://doi.org/10.18653/v1/2023.emnlp-main.495",
  "title": "Active Retrieval Augmented Generation",
  "authors": ["Zhengbao Jiang", "Frank F. Xu", "Luyu Gao", "Zhiqing Sun", "Qian Liu"],
  "year": 2023,
  "publicationDate": "2023-01-01",
  "venue": "Conference on Empirical Methods in Natural Language Processing (EMNLP)",
  "type": "conference-paper",
  "citedByCount": 497,
  "isOpenAccess": true,
  "oaStatus": "hybrid",
  "license": "cc-by",
  "landingPageUrl": "https://doi.org/10.18653/v1/2023.emnlp-main.495",
  "pdfUrl": "https://aclanthology.org/2023.emnlp-main.495.pdf",
  "ids": {"openalex": "https://openalex.org/W4389519118", "doi": "https://doi.org/10.18653/v1/2023.emnlp-main.495", "pmid": null, "pmcid": null, "arxiv": null},
  "abstract": "Despite the remarkable ability of large language models...",
  "fullText": "# Active Retrieval Augmented Generation\n\n...",
  "fullTextUrl": "https://aclanthology.org/2023.emnlp-main.495.pdf",
  "fullTextError": null,
  "truncated": false,
  "attribution": "\"Active Retrieval Augmented Generation\" by Zhengbao Jiang, Frank F. Xu, Luyu Gao et al., Conference on Empirical Methods in Natural Language Processing (EMNLP) (2023). License: CC BY (https://creativecommons.org/licenses/by/), for the copy at https://doi.org/10.18653/v1/2023.emnlp-main.495. https://doi.org/10.18653/v1/2023.emnlp-main.495. Metadata: OpenAlex (CC0)."
}
```

- A missing field is `null`. `license` is the license of the open copy the text comes from, as OpenAlex reports it.
- Without an open license that allows reuse, `abstract` and `fullText` are `null` and `fullTextError` says why; the paper is still delivered with its metadata.
- Full text is read only from the open copy's PDF, and only on sites whose terms allow automated downloads (for example ACL Anthology, PLOS, eLife, Zenodo). For any other site, including arXiv and PubMed Central, the item gives the link in `fullTextUrl` and says why in `fullTextError`. Scanned PDFs (images only) are not read.
- An ID that could not be delivered has `input` and `error`, with the reason, and is not charged.
- The run's status message says how many papers were delivered, how many with full text, how many failed and why the run stopped early, if it did.
- If nothing is delivered, the run still ends as succeeded: each paper that failed, or a search that found nothing or could not be run, is in the dataset with its `input` and `error`, the status message gives the first reason, and nothing was charged.

### Input

| Field | What it does |
|---|---|
| `query` | What to search: topic, title words or author, up to 300 characters. |
| `ids` | From 1 to 100 IDs: DOIs, arXiv IDs, PMIDs, PMCIDs or OpenAlex IDs. A repeated ID is read once. When given, the search is not run. |
| `maxResults` | From 1 to 100 (default 10): how many papers the search returns. |
| `fullText` | Also read the full text when the license allows it (on by default). |
| `openAccessOnly` | Search only papers that have a free copy. |
| `fromYear` | Search only papers published in or after this year. |

### Limits

- PDFs up to 5 MB, 15 s per download attempt and 30 s to convert each; 3 papers at a time. A download that runs out of time, cannot connect or gets a server error is tried once more, except on sites that ask for a pause between downloads; if that fails too, the paper comes back without its text and the text is not charged.
- One PDF per run from sites that ask crawlers to wait between requests.
- Set a maximum charge per run to cap spending: the run stops before a paper that would pass it.

### Pricing

This actor bills two events, nothing else:

- `paper`: one per paper delivered with its metadata.
- `full-text`: one more per paper delivered with its full text as markdown.

IDs that are not found, papers that cannot be read and full texts that cannot be read are not charged.

### Site owners

PDFs are read as the `FrameskimFetch` bot, which respects `robots.txt` on every request. To keep your PDFs out, disallow `FrameskimFetch` in your `robots.txt` (the other Frameskim actors that fetch pages also honor that user agent, so the rule stops them too). Rights holders can also write to support@frameskim.dev. Neither a `robots.txt` rule nor a request removes text from datasets that users already hold.

### Terms and privacy

Research Papers to Markdown for AI Agents is operated by Emttn LLC and is not affiliated with, endorsed by or sponsored by OpenAlex or OurResearch, arXiv, the U.S. National Library of Medicine or PubMed Central, or the publishers, repositories and authors of the papers it returns. You are responsible for following each paper's license when you reuse its metadata, abstract or text; the license shown comes from OpenAlex and may be wrong, so check it on the paper's own page. Items carry the authors' names, public bibliographic data, so you can give the attribution the license asks for. Terms: https://frameskim.dev/terms. Privacy: https://frameskim.dev/privacy. Questions: support@frameskim.dev.

Not affiliated with the International DOI Foundation; DOI is named here only as the identifier you look papers up by.

### Support

Every error says what was wrong. For anything else, see https://frameskim.dev/terms.

# Actor input Schema

## `query` (type: `string`):

Topic, title words or author to search for, up to 300 characters. Leave empty to look papers up by ID.

## `ids` (type: `array`):

DOIs, arXiv IDs, PubMed IDs (PMID), PubMed Central IDs (PMC...) or OpenAlex IDs (W...), from 1 to 100. When given, the search is not run.

## `maxResults` (type: `integer`):

How many papers the search returns, from 1 to 100.

## `fullText` (type: `boolean`):

Also read the paper's full text when its open license allows it and its PDF is on a site that allows automated downloads. Each item with full text is one more event.

## `openAccessOnly` (type: `boolean`):

Search only papers that have a free copy.

## `fromYear` (type: `integer`):

Search only papers published in or after this year.

## `failWhenEmpty` (type: `boolean`):

Internal: the run ends as failed, instead of succeeded with error items, when no paper is delivered. Used by health checks.

## Actor input object example

```json
{
  "query": "retrieval augmented generation",
  "maxResults": 10,
  "fullText": true,
  "openAccessOnly": false,
  "failWhenEmpty": false
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset items: id, doi, title, authors, year, publicationDate, venue, type, citedByCount, isOpenAccess, oaStatus, license, landingPageUrl, pdfUrl, ids, abstract, fullText, fullTextUrl, fullTextError, truncated and attribution; failed IDs carry input and error.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "retrieval augmented generation"
};

// Run the Actor and wait for it to finish
const run = await client.actor("emttn/research-papers-markdown").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "query": "retrieval augmented generation" }

# Run the Actor and wait for it to finish
run = client.actor("emttn/research-papers-markdown").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "retrieval augmented generation"
}' |
apify call emttn/research-papers-markdown --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,emttn/research-papers-markdown"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/NUqndYLNgFPCk7d4E/builds/wOqCXVg9qQEK9vNJZ/openapi.json