Facebook Comments Data
Pricing
$0.25 / 1,000 Comments
Facebook Comments Data
Our Facebook Comments Scraper extracts real-time comments from Facebook posts, including text, timestamp, author details, engagement metrics, and other insights. Download the data in formats such as JSON, CSV, Excel, or XML. Fast, accurate, and designed for in-depth analysis and actionable insights.
0.0 (0)
Pricing
$0.25 / 1,000 Comments
0
Monthly users
3
Runs succeeded
>99%
Last modified
6 days ago
You can access the Facebook Comments Data 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.
1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=axesso_data/facebook-comments-data"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1faUsing Facebook Comments Data via Model Context Protocol (MCP) server
MCP server lets you use Facebook Comments Data within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the Facebook Comments Data Actor with the provided input.
1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2 "jsonrpc": "2.0",
3 "id": 1,
4 "method": "tools/call",
5 "params": {
6 "arguments": {
7 "input": [
8 {
9 "feedbackId": "ZmVlZGJhY2s6Njg5OTU1OTc3MDI2OTQ5",
10 "maxComments": 50
11 },
12 {
13 "feedbackId": "ZmVlZGJhY2s6NjkxNjYxNzIwMTg5NzA4",
14 "maxComments": 50
15 }
16 ]
17},
18 "name": "axesso_data/facebook-comments-data"
19 }
20}'The response should be: Accepted. You should received response via SSE (JSON) as:
1event: message
2data: {
3 "result": {
4 "content": [
5 {
6 "type": "text",
7 "text": "ACTOR_RESPONSE"
8 }
9 ]
10 }
11}Configure local MCP Server via standard input/output for Facebook Comments Data
You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:
1{
2 "mcpServers": {
3 "actors-mcp-server": {
4 "command": "npx",
5 "args": [
6 "-y",
7 "@apify/actors-mcp-server",
8 "--actors",
9 "axesso_data/facebook-comments-data"
10 ],
11 "env": {
12 "APIFY_TOKEN": "<YOUR_API_TOKEN>"
13 }
14 }
15 }
16}You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.
To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.
Pricing
Pricing model
Pay per resultThis Actor is paid per result. You are not charged for the Apify platform usage, but only a fixed price for each dataset of 1,000 items in the Actor outputs.
Price per 1,000 items
$0.25
