# DBLP Publications Scraper (`parseforge/dblp-publications-scraper`) Actor

Scrapes DBLP computer science publications by author, title, or keyword and returns each paper as a flat row with title, authors, venue, year, and DOI.

- **URL**: https://apify.com/parseforge/dblp-publications-scraper.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** Developer tools, Automation, Other
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.52 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

[![ParseForge](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner.jpg)](https://apify.com/parseforge?fpr=vmoqkp)

### DBLP Publications Scraper

**Scrape DBLP computer science publications by author, title, or keyword, up to a million per run.** Each publication comes with its title, authors, venue, year, and DOI. No API key or login. Export to CSV, JSON, Excel, or XML.

DBLP is the largest open bibliography of computer science, with millions of papers from journals, conferences, and workshops. This Actor searches DBLP by author, title, or keyword and returns each matching publication as a flat row, ready for analysis. No API key, no login, no rate limits.

| Who uses it | What they scrape DBLP for |
|---|---|
| Academic researchers | Build a literature review dataset for a specific topic or author |
| Data scientists | Analyze publication trends across venues and years |
| Librarians | Compile bibliographies for computer science courses |
| Recruiters | Find authors with expertise in a niche area |

### What it does

This Actor collects DBLP publications matching a search query and returns each one as a flat row with title, authors, venue, year, and DOI.

- 🔍 **Search by query:** author name, title fragment, or keyword like "deep learning" or "quantum computing".
- 📄 **Flat row output:** each publication is one row with title, authors, venue, year, and DOI.
- 📊 **Bulk collection:** set maximum publications up to 1,000,000 per run.
- 💾 **Multiple export formats:** CSV, JSON, Excel, and XML.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

### What you can do with DBLP data

**📚 Build a literature review dataset.**

A PhD student enters a research topic like "graph neural networks" and collects all matching publications to identify key papers and authors.

**📈 Analyze publication trends.**

A data scientist scrapes publications for a set of keywords over several years to track the rise and fall of research areas.

**👥 Find experts in a niche.**

A recruiter searches for an author name or a specialized keyword to locate researchers with the right expertise.

**🗂️ Compile a bibliography.**

A librarian collects all publications from a specific venue or author to create a reading list for a course.

### Why choose this scraper

| | What you get |
|---|---|
| **No API key** | DBLP's public search is used directly, so you don't need to register or authenticate. |
| **Structured data** | Every publication is returned as a flat row with consistent fields, ready for spreadsheets or databases. |
| **Scalable** | Collect up to a million publications per run, enough for large-scale bibliometric studies. |
| **Flexible query** | Search by author, title, or keyword to target exactly the publications you need. |

### How it compares

This Actor focuses on searching DBLP publications by a single query and returning a flat list, while the competitors below offer additional features like scraping authors and venues separately.

| Feature | ParseForge | DBLP Scraper - Publications, Authors & Venues | DBLP Computer Science Publication Search |
|---|---|---|---|
| Search by keyword | Yes | Yes | Yes |
| Search by author | Yes | Yes | Yes |
| Search by title | Yes | Not listed | Not listed |
| Scrape authors separately | Not listed | Yes | Not listed |
| Scrape venues separately | Not listed | Yes | Not listed |
| Filter by year | Not listed | Not listed | Yes |
| Filter by venue | Not listed | Not listed | Yes |

### Configure the run

Drive the Actor with a single search query and a maximum number of publications. The query can be an author name, a title fragment, or a keyword, and the Actor returns the most relevant matches from DBLP. The Input tab lists every parameter.

A first run with the defaults:

```json
{
 "query": "deep learning",
 "maxItems": 10
}
```

A larger pull:

```json
{
 "query": "deep learning",
 "maxItems": 200
}
```

### Pricing

Pay-per-result: **$0.005 per result** collected. You pay only for the results written to your dataset.

| Results collected | Approximate cost |
|---|---|
| 100 results | $0.50 |
| 1,000 results | $5.00 |
| 10,000 results | $50.00 |

New Apify accounts start with $5 in free credit.

### Free users

Free-plan runs return up to 10 results as a preview. [Upgrade your Apify plan](https://console.apify.com/sign-up?fpr=vmoqkp) to collect up to 1,000,000 results per run.

### Run it

1. [Create a free Apify account with $5 in credit](https://console.apify.com/sign-up?fpr=vmoqkp).
2. Open the [DBLP Publications Scraper](https://apify.com/parseforge/dblp-publications-scraper?fpr=vmoqkp).
3. Set your inputs and any filters, then click **Start**.
4. Export the results as CSV, Excel, JSON, or XML from the **Dataset** tab.

Run it programmatically through the [Apify API](https://docs.apify.com/api/v2) (`run-sync-get-dataset-items`) or the [ApifyClient](https://docs.apify.com/api/client/js) for JavaScript and Python.

### Use with AI agents (MCP)

Give an AI agent live access to DBLP through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

```bash
claude mcp add --transport http apify "https://mcp.apify.com/?tools=parseforge/dblp-publications-scraper"
```

Then prompt it in plain language to run the scraper and read back the results.

### Troubleshooting

**Why am I getting no results?**

Check your query for typos or try a broader term. DBLP's search may not return results for very specific phrases. Also ensure that the query is not empty.

**Why did the run stop before reaching my maximum?**

The Actor stops when there are no more matching publications on DBLP. If you expected more results, try a different query or a broader keyword.

**Can I search for multiple authors at once?**

No, the Actor accepts a single query string. To search for multiple authors, run the Actor multiple times with different queries or use a comma-separated list if DBLP supports it.

**Why are some fields empty in the output?**

DBLP may not have complete metadata for every publication. For example, some older papers may lack a DOI. Empty fields are normal and reflect the source data.

**How do I get more than 1,000,000 publications?**

The maximum is 1,000,000 per run. If you need more, you can split your query into smaller chunks, for example by year or venue, and run the Actor multiple times.

### FAQ

| Question | Answer |
|---|---|
| What is DBLP? | DBLP is the largest open bibliography of computer science publications, indexing millions of papers from journals, conferences, and workshops. It is maintained by Schloss Dagstuhl and is free to use. |
| Do I need an API key or login? | No. This Actor uses DBLP's public search interface directly, so you don't need to register or authenticate. |
| What can I search for? | You can search by author name, title fragment, or keyword. For example, "deep learning", "quantum computing", or "Alan Turing". |
| How many publications can I collect? | You can set the maximum publications per run from 1 up to 1,000,000. The Actor will stop when it reaches that number or when there are no more matches. |
| What data do I get for each publication? | Each publication is returned as a flat row with fields like title, authors, venue, year, and DOI. The exact fields are shown in the sample output. |
| Can I export the results? | Yes, you can export the dataset in CSV, JSON, Excel, or XML format from the Apify platform. |
| Is this Actor free? | The Actor itself is free to use on Apify. You only pay for the platform usage if you exceed the free tier limits. |
| How do I run this Actor? | You can run it from the Apify console by entering a query and a maximum number of publications, or you can call it via the API. |
| Can I schedule this Actor to run regularly? | Yes, you can set up a schedule in Apify to run the Actor at intervals, for example daily or weekly, to keep your dataset up to date. |
| What is the difference between this Actor and the DBLP Scraper by logiover? | This Actor focuses on searching publications by a single query and returning a flat list. The other Actor may offer additional features like scraping authors and venues separately. Check the feature comparison table for details. |

### Related actors

Browse the full [ParseForge collection](https://apify.com/parseforge?fpr=vmoqkp) for more scrapers.

🆘 **Need help?** Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ **Disclaimer.** This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Schloss Dagstuhl - Leibniz Center for Informatics. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.

# Actor input Schema

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

The search term for publications (for example "deep learning", "quantum computing", or an author name).

## `maxItems` (type: `integer`):

How many publications to collect per run.

## Actor input object example

```json
{
  "query": "deep learning",
  "maxItems": 10
}
```

# Actor output Schema

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

No description

# 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": "deep learning",
    "maxItems": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/dblp-publications-scraper").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": "deep learning",
    "maxItems": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("parseforge/dblp-publications-scraper").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": "deep learning",
  "maxItems": 10
}' |
apify call parseforge/dblp-publications-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,parseforge/dblp-publications-scraper"
        }
    }
}

```

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/1rxqgkM4EvExOHFwi/builds/amu2Z6jFkD6NAhupp/openapi.json