Instagram Comments Scraper

Pricing

from $2.20 / 1,000 results

Try for free

Go to Apify Store

Instagram Comments Scraper

Try for free

The Instagram Comments Scraper is a tool designed to extract detailed comments from valid Instagram posts and reels. This actor provides a structured way to gather insights from user interactions on Instagram, making it easier to analyze engagement and sentiment.

Pricing

from $2.20 / 1,000 results

Rating

5.0

(1)

Developer

Pratik Dani

Maintained by Community

Actor stats

Bookmarked

297

Total users

Monthly active users

a month ago

Last modified

Categories

Social media

Developer tools

Automation

You can access the Instagram Comments 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.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

{
  "openapi": "3.0.1",
  "info": {
    "version": "0.0",
    "x-build-id": "H0z5KgB8kh3f8LBSp"
  },
  "servers": [
    {
      "url": "https://api.apify.com/v2"
    }
  ],
  "paths": {
    "/acts/pratikdani~instagram-comments-scraper/run-sync-get-dataset-items": {
      "post": {
        "operationId": "run-sync-get-dataset-items-pratikdani-instagram-comments-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": {
                "$ref": "#/components/schemas/inputSchema"
              }
            }
          }
        },
        "parameters": [
          {
            "name": "token",
            "in": "query",
            "required": true,
            "schema": {
              "type": "string"
            },
            "description": "Enter your Apify token here"
          }
        ],
        "responses": {
          "200": {
            "description": "OK"
          }
        }
      }
    },
    "/acts/pratikdani~instagram-comments-scraper/runs": {
      "post": {
        "operationId": "runs-sync-pratikdani-instagram-comments-scraper",
        "x-openai-isConsequential": false,
        "summary": "Executes an Actor and returns information about the initiated run in response.",
        "tags": [
          "Run Actor"
        ],
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$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": {
                  "$ref": "#/components/schemas/runsResponseSchema"
                }
              }
            }
          }
        }
      }
    },
    "/acts/pratikdani~instagram-comments-scraper/run-sync": {
      "post": {
        "operationId": "run-sync-pratikdani-instagram-comments-scraper",
        "x-openai-isConsequential": false,
        "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
        "tags": [
          "Run Actor"
        ],
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$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": [
          "url"
        ],
        "properties": {
          "url": {
            "title": "Instagram Posts/Reels Url",
            "type": "string",
            "description": "URL of the Instagram Post/Reel"
          }
        }
      },
      "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
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}

Instagram Comments 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 Instagram Comments Scraper from the options below:

OpenAPI.json

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:

Instagram Comments Scraper API in Python

Instagram Comments Scraper API in JavaScript

Instagram Comments Scraper API through CLI

Instagram Comments Scraper API

Instagram Comments Scraper

devil_port369-owner/instagram-comments-scraper

Scrape Instagram comments safely and efficiently with this Apify Actor. Extract comment text, usernames, and timestamps from public posts/reels for insights and analysis.

DataFusionX

1.0

Instagram Comments Scraper

scrapier/instagram-comments-scraper

Scrape Instagram post comments with the Instagram Comments Scraper. Extract usernames, comment text, likes, replies, and timestamps. Ideal for engagement analysis, sentiment tracking, and audience insights. Fast, reliable, and scalable for single posts or bulk scraping.

Scrapier

Instagram Comments Scraper

scraper-engine/instagram-comments-scraper

The Instagram Comments Scraper extracts comments from posts or reels, capturing usernames, text, timestamps, and engagement metrics. Ideal for social listening, sentiment analysis, and audience research, it delivers clean, structured data for insights, analytics, or API integration.

Scraper Engine

Instagram Comments Scraper

simpleapi/instagram-comments-scraper

Instagram Comments Scraper extracts comments from any public Instagram post, including usernames, comment text, timestamps, likes, replies, and comment IDs. Perfect for sentiment analysis, audience research, trend monitoring, and automating large-scale Instagram comment data collection.

SimpleAPI

Instagram Comments Super Scraper

muhammad_noman_riaz/instagram-comments-super-scraper

The Instagram Comments Super Scraper is a powerful automation tool designed to extract detailed comment data from Instagram posts and reels. Whether you’re conducting social media research, performing sentiment analysis, or tracking engagement trends, this scraper delivers everything you need.

Muhammad Noman Riaz

Instagram Post comments Scraper

bhansalisoft/instagram-post-comments-scraper

Instagram Post comments Scraper - scrap all instagram post comments with all details with instagram username and userid. you just need to insert post short code then tool will scrape all post comments related to this post

bhansalisoft

121

1.0

🏯 Instagram Comments Scraper (Pay Per Result)

apidojo/instagram-comments-scraper

The Instagram Comments Scraper is the perfect tool for extracting comments from Instagram posts quickly and affordably. Priced at just $0.50 per 1,000 comments, it offers impressive speeds, processing 100 to 200 comments per second!

API Dojo

1.3K

3.1

Instagram Comments Scraper

api-empire/instagram-comments-scraper

Instagram Comments Scraper extracts comments from any public Instagram post. Capture usernames, text, timestamps, likes, and replies in structured format. Ideal for sentiment analysis, research, audience insights, and automated workflows needing clean comment data.

API Empire

Instagram post & comments Scraper

logical_scrapers/instagram-post-comments-scraper

The only Instagram scraper that can get you all comments. scrapes full post data including metadata and comments from Instagram posts. It takes Instagram post URLs as input and extracts detailed post information with support for authentication.

Goldmine

4.8

Instagram Comments Scraper

easyapi/instagram-comments-scraper

Effortlessly extract comments from Instagram posts. Capture user details, engagement metrics, and nested replies. Perfect for social media analysis, influencer research, and brand monitoring. Stealth-enabled for reliable data collection.