# Academic Paper Search MCP: arXiv, Crossref & OpenAlex (`noisy_jubilee/paper-search-mcp`) Actor

Search arXiv, Crossref and OpenAlex papers, look up a DOI or arXiv id with abstract, and get cited-by and reference lists. Batch runs or MCP server for agents.

- **URL**: https://apify.com/noisy_jubilee/paper-search-mcp.md
- **Developed by:** [Stephen](https://apify.com/noisy_jubilee) (community)
- **Categories:** AI, MCP servers, Developer tools
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $8.00 / 1,000 paper searches

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## Academic Paper Search MCP: arXiv, Crossref & OpenAlex

Search and look up scholarly papers from three open sources, in one Actor:

- **Search papers** by keywords on **arXiv** (preprints), **Crossref** (DOIs registered by publishers) or **OpenAlex** (open index of scholarly works), with an optional publication date range and sort by relevance or newest.
- **Get a paper** by **DOI**, **arXiv id** or **OpenAlex id**: title, authors, date, venue, type, DOI, arXiv id, landing page and PDF links, open-access flag, citation count and abstract (when the source has one). DOI lookups merge Crossref and OpenAlex; arXiv lookups merge arXiv and OpenAlex.
- **Citations**: list the papers that **cite** a paper, or the papers it **references**, ranked by citation count or date (OpenAlex citation graph).

Use it for literature reviews, research agents and RAG pipelines, citation checks of LLM output, or enriching a list of DOIs. **No API key needed.** Runs as a normal batch Actor or as an **MCP server** for AI agents.

### Quick start

1. Enter one or more **search queries** and/or **paper ids** (the prefill searches "large language model evaluation" on Crossref and looks up the DOI `10.1038/nature14539`).
2. Optionally choose the **source**, a **date range**, and **citations** (cited by / references) for each paper id.
3. Click **Start**. You get one dataset row per paper.

### Input

| Field | Default | Meaning |
|---|---|---|
| `queries` | – | Keyword searches, one per line (max 300 characters). arXiv field syntax works with source arXiv: `ti:transformer AND cat:cs.CL` |
| `source` | `crossref` | `crossref`, `openalex` or `arxiv` |
| `maxResultsPerQuery` | 10 | 1–50 papers per query |
| `fromDate` / `toDate` | – | `YYYY`, `YYYY-MM` or `YYYY-MM-DD` |
| `sort` | `relevance` | `relevance` or `date` (newest first) |
| `paperIds` | – | DOIs, arXiv ids, OpenAlex ids or doi.org / arxiv.org / openalex.org links |
| `citations` | `none` | `cited_by` or `references` for each paper id |
| `maxCitationsPerPaper` | 10 | 1–50 |
| `includeAbstracts` | `true` | Return abstracts where available |
| `openalexApiKey` | – | Optional free OpenAlex key for higher OpenAlex limits |

Up to 1,000 queries and 1,000 paper ids per run. With an empty input the Actor runs the prefill example (one Crossref search and one DOI lookup).

### Output

One dataset row per paper. `kind` says where it comes from: `search`, `paper`, `cited_by` or `references`.

Fields: `title`, `authors` (first 25), `authorCount`, `published`, `year`, `venue`, `type`, `doi`, `arxivId`, `openalexId`, `url`, `pdfUrl`, `abstract`, `citedByCount`, `categories` (arXiv categories or OpenAlex topics), `isOpenAccess`, `source`, plus `query` / `input` / `ofPaper`, `rank` and a `credit` line.

```json
{
  "kind": "paper", "input": "10.1038/nature14539", "sources": ["crossref", "openalex"],
  "title": "Deep learning", "authors": ["Yann LeCun", "Yoshua Bengio", "Geoffrey Hinton"], "published": "2015-05-27",
  "venue": "Nature", "doi": "10.1038/nature14539", "openalexId": "W2919115771", "citedByCount": 84105, "isOpenAccess": true
}
```

A `SUMMARY` record in the key-value store gives counts, charges and any errors.

### Pricing (pay per event)

| Event | Price |
|---|---|
| Paper search (one query with results, up to 50 papers) | $0.008 |
| Paper lookup (one paper found by id) | $0.004 |
| Citation list (one paper's citing or referenced papers, up to 50) | $0.008 |
| Actor start (Apify standard, once per run) | $0.0003 |

Searches with no results, ids that are not found, and upstream errors are **not charged**. The run stops cleanly when your maximum charge per run is reached.

### Use it as an MCP server (AI agents)

The same tools are available as a **Model Context Protocol (MCP) server** over streamable HTTP for Claude, Cursor, VS Code or any MCP client:

- **Endpoint:** `https://noisy-jubilee--paper-search-mcp.apify.actor/mcp`
- **Auth:** header `Authorization: Bearer <your Apify API token>`

| MCP tool | Arguments | Charged event |
|---|---|---|
| `search_papers` | `query`, `source`, `fromDate`, `toDate`, `limit`, `sort`, `includeAbstracts` | `paper-search` (only if results) |
| `get_paper` | `id` (DOI / arXiv / OpenAlex) | `paper-lookup` (only if found) |
| `get_citations` | `id`, `direction` (`cited_by` / `references`), `limit`, `sort`, `includeAbstracts` | `citation-list` (only if results) |

Listing tools is free. Example client config:

```json
{ "mcpServers": { "papers": { "url": "https://noisy-jubilee--paper-search-mcp.apify.actor/mcp",
  "headers": { "Authorization": "Bearer <APIFY_TOKEN>" } } } }
```

### Speed and limits

- **Crossref** and **OpenAlex** answers usually take 0.5–3 seconds.
- The MCP server lets one server instance handle many concurrent calls, so arXiv requests from one user go through a single 1-request-per-3-seconds queue instead of many parallel instances.
- **arXiv** asks API users to send at most one request every 3 seconds, so arXiv calls are queued and can take several seconds (sometimes 15–30 s when the arXiv API is busy). If arXiv answers "Rate exceeded", the Actor waits 5 seconds and retries once; if it is still busy you get a "rate limit" error and are not charged. For broad searches, Crossref or OpenAlex is faster.
- Abstracts depend on the publisher: Crossref and OpenAlex do not have abstracts for every paper (`abstract` is then `null`).
- Citation counts come from OpenAlex (or Crossref when OpenAlex has no record) and can differ from Google Scholar.

### Data sources and credits

Thank you to arXiv for use of its open access interoperability. This Actor is not affiliated with or endorsed by arXiv, Crossref or OpenAlex.

- **arXiv API** – metadata is CC0. Each result links to its arXiv abstract page.
- **Crossref REST API** – public metadata about scholarly works; abstracts remain under the publisher's copyright where applicable.
- **OpenAlex** – CC0 data.

The Actor only reads public metadata APIs, respects each API's rate limits, and caches repeated lookups for an hour.

# Actor input Schema

## `queries` (type: `array`):

Keywords to search for, one search per line (max 300 characters each). For arXiv you can also use its field syntax, e.g. ti:transformer AND cat:cs.CL.

## `source` (type: `string`):

Index to search. Crossref: DOI metadata registered by publishers. OpenAlex: open scholarly index with citation counts and abstracts. arXiv: preprints in physics, maths, CS and more (arXiv allows one request every 3 seconds, so arXiv searches are slower).

## `maxResultsPerQuery` (type: `integer`):

Papers to return for each query (1-50).

## `fromDate` (type: `string`):

Only papers published on or after this date: YYYY, YYYY-MM or YYYY-MM-DD.

## `toDate` (type: `string`):

Only papers published on or before this date: YYYY, YYYY-MM or YYYY-MM-DD.

## `sort` (type: `string`):

Order search results by relevance or newest first.

## `paperIds` (type: `array`):

Papers to look up: DOIs (10.1038/nature14539, https://doi.org/...), arXiv ids (2401.01234, arXiv:hep-th/9901001, arxiv.org/abs/... links) or OpenAlex ids (W2919115771). Each returns title, authors, date, venue, abstract, citation count and links.

## `citations` (type: `string`):

Also list papers that cite each paper id (cited by, most-cited first) or the papers it references. Uses OpenAlex.

## `maxCitationsPerPaper` (type: `integer`):

Citing or referenced papers to return per paper id (1-50).

## `includeAbstracts` (type: `boolean`):

Return abstracts where the source has them (some publishers do not share abstracts).

## `openalexApiKey` (type: `string`):

Your free OpenAlex key (openalex.org/settings/api) for higher OpenAlex limits. Not needed for normal use.

## Actor input object example

```json
{
  "queries": [
    "large language model evaluation",
    "CRISPR off-target"
  ],
  "source": "crossref",
  "maxResultsPerQuery": 5,
  "sort": "relevance",
  "paperIds": [
    "10.1038/nature14539",
    "1706.03762"
  ],
  "citations": "none",
  "maxCitationsPerPaper": 10,
  "includeAbstracts": true
}
```

# Actor output Schema

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

One row per paper: search results, looked-up papers and citing / referenced papers.

## `summary` (type: `string`):

SUMMARY record in the default key-value store: counts, charges, errors and status of the run.

# 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 = {
    "queries": [
        "large language model evaluation"
    ],
    "maxResultsPerQuery": 5,
    "paperIds": [
        "10.1038/nature14539"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("noisy_jubilee/paper-search-mcp").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 = {
    "queries": ["large language model evaluation"],
    "maxResultsPerQuery": 5,
    "paperIds": ["10.1038/nature14539"],
}

# Run the Actor and wait for it to finish
run = client.actor("noisy_jubilee/paper-search-mcp").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 '{
  "queries": [
    "large language model evaluation"
  ],
  "maxResultsPerQuery": 5,
  "paperIds": [
    "10.1038/nature14539"
  ]
}' |
apify call noisy_jubilee/paper-search-mcp --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,noisy_jubilee/paper-search-mcp"
        }
    }
}
```

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/PKwad7f4AgUKz3MkK/builds/aympuERKxuqPHDO83/openapi.json