Facebook Search Posts

Search public Facebook posts by keyword. Returns post content, author details, engagement metrics, and media attachments.

Endpoint

GET /v1/facebook/posts

Price: $0.008 per page Free tier: 50 requests/month

Parameters

Parameter	Required	Description
`query`	Yes	Search keyword (max 500 characters)
`pages`	No	Number of pages to fetch (1-10, default 1). Billed per page.
`start_date`	No	Filter posts from this date onward (format: `YYYY-MM-DD`)
`end_date`	No	Filter posts up to this date (format: `YYYY-MM-DD`)
`sort_by`	No	Sort order: `most_recent` or `relevance` (default: `relevance`)

Response Fields

Field	Type	Description
`posts`	array	Array of matching posts
`posts[].post_id`	string	Unique post identifier
`posts[].url`	string	Direct link to the post
`posts[].message`	string	Post text content
`posts[].date`	string	Publication date and time
`posts[].timestamp`	integer	Unix timestamp of publication
`posts[].author_name`	string	Name of the post author
`posts[].author_id`	string	Unique identifier of the author
`posts[].author_url`	string	Link to the author’s profile
`posts[].author_profile_picture`	string	URL of the author’s profile picture
`posts[].comments_count`	integer	Number of comments
`posts[].reactions_count`	integer	Total number of reactions
`posts[].reshare_count`	integer	Number of reshares
`posts[].reactions`	object	Breakdown of reaction types and counts
`posts[].image_url`	string/null	URL of attached image, if any
`posts[].video`	string/null	URL to attached video, if any
`posts[].external_url`	string/null	External link shared in the post, if any
`count`	integer	Number of posts returned
`pages`	integer	Number of pages fetched

Example Request

cURL

curl "https://apidirect.io/v1/facebook/posts?query=artificial%20intelligence" \
  -H "X-API-Key: YOUR_API_KEY"

Python

import requests

response = requests.get(
    "https://apidirect.io/v1/facebook/posts",
    headers={"X-API-Key": "YOUR_API_KEY"},
    params={
        "query": "artificial intelligence"
    }
)
print(response.json())

Example Response

{
  "posts": [
    {
      "post_id": "pfbid02kWx7vN9mJqR4hLcT3bY",
      "url": "https://www.facebook.com/permalink.php?story_fbid=pfbid02kWx7vN9mJqR4hLcT3bY&id=100064837291045",
      "message": "Artificial intelligence is transforming the way we approach medical diagnostics. A new study shows AI models can now detect early-stage cancers with 94% accuracy, outperforming traditional screening methods.",
      "date": "2025-03-09 11:20:00",
      "timestamp": 1741519200,
      "author_name": "TechNews Daily",
      "author_id": "100064837291045",
      "author_url": "https://www.facebook.com/TechNewsDaily",
      "author_profile_picture": "https://scontent.fxxx.fbcdn.net/v/t1.6435-1/profile_pic.jpg",
      "comments_count": 156,
      "reactions_count": 842,
      "reshare_count": 203,
      "reactions": {
        "like": 512,
        "love": 187,
        "wow": 98,
        "haha": 5,
        "sad": 12,
        "angry": 3,
        "care": 25
      },
      "image_url": "https://scontent.fxxx.fbcdn.net/v/t39.30808-6/ai_diagnostics.jpg",
      "video": null,
      "external_url": "https://technewsdaily.com/ai-cancer-detection-study"
    }
  ],
  "count": 20,
  "pages": 1
}