Medium Publication Scraper avatar
Medium Publication Scraper

Pricing

$5.00 / 1,000 results

Go to Store
Medium Publication Scraper

Medium Publication Scraper

Developed by

AutomateLab

AutomateLab

Maintained by Community

The ONLY Publication-Focused Medium Analytics Platform - Extract comprehensive data from Medium's top publications and authors. No API key required, instant access to the world's largest professional publishing platform!

0.0 (0)

Pricing

$5.00 / 1,000 results

0

Total users

3

Monthly users

3

Runs succeeded

>99%

Last modified

2 days ago

You can access the Medium Publication Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

{
"openapi": "3.0.1",
"info": {
"version": "1.0",
"x-build-id": "Vg0DmtgZxGvEDl28V"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/red.cars~medium-publication-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-red.cars-medium-publication-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/red.cars~medium-publication-scraper/runs": {
"post": {
"operationId": "runs-sync-red.cars-medium-publication-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/red.cars~medium-publication-scraper/run-sync": {
"post": {
"operationId": "run-sync-red.cars-medium-publication-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"mode"
],
"properties": {
"mode": {
"title": "Scraping Mode",
"enum": [
"publication",
"author",
"articles",
"trending",
"tags",
"bulk"
],
"type": "string",
"description": "Choose what type of Medium data to extract",
"default": "publication"
},
"urls": {
"title": "Medium URLs",
"maxItems": 100,
"type": "array",
"description": "List of Medium URLs to scrape. Supports @username, @publication, and article URLs.",
"items": {
"type": "string"
}
},
"publications": {
"title": "Publication Names",
"maxItems": 50,
"type": "array",
"description": "List of Medium publication handles (e.g., @towards-data-science, @freecodecamp).",
"default": [
"towards-data-science",
"freecodecamp"
],
"items": {
"type": "string"
}
},
"authors": {
"title": "Author Usernames",
"maxItems": 50,
"type": "array",
"description": "List of Medium author handles (e.g., @tim, @medium).",
"default": [
"tim",
"medium"
],
"items": {
"type": "string"
}
},
"tags": {
"title": "Topic Tags",
"maxItems": 20,
"type": "array",
"description": "List of Medium topic tags to analyze (e.g., artificial-intelligence, startup, programming).",
"default": [
"artificial-intelligence",
"startup",
"programming"
],
"items": {
"type": "string"
}
},
"maxArticles": {
"title": "Max Articles per Source",
"minimum": 1,
"maximum": 1000,
"type": "integer",
"description": "Maximum number of articles to extract per publication/author",
"default": 100
},
"includeContent": {
"title": "Include Full Article Content",
"type": "boolean",
"description": "Extract complete article text content (may slow down scraper significantly)",
"default": false
},
"includeMetrics": {
"title": "Include Engagement Metrics",
"type": "boolean",
"description": "Extract claps, responses, and reading time data",
"default": true
},
"includeAuthorInfo": {
"title": "Include Author Details",
"type": "boolean",
"description": "Extract detailed author information and follower counts",
"default": true
},
"extractionDepth": {
"title": "Extraction Depth",
"enum": [
"basic",
"standard",
"comprehensive"
],
"type": "string",
"description": "How deep to extract data from each source",
"default": "standard"
},
"maxResults": {
"title": "Max Total Results",
"minimum": 1,
"maximum": 5000,
"type": "integer",
"description": "Maximum total number of items to extract across all sources",
"default": 500
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}

Medium Publication Scraper OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for Medium Publication Scraper from the options below:

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients: