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47 tools across Facebook and Instagram. Every tool maps 1:1 to a REST endpoint on `api.socialapis.io` — pricing notes in each tool description indicate per-call credit cost.
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### Facebook — Pages
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-`facebook_get_page_id` — Extract page ID from URL
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-`facebook_get_page_details` — Page info, followers, likes, category. Set `exact_followers_count=true` for the exact integer (charges 5 credits instead of 1)
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-`facebook_get_page_posts` — Fetch posts with `after_time` / `before_time` for date filtering. `limit` 3-9, charges scale per `ceil(returned / 3)`
-`instagram_get_location_posts` — Posts tagged at a specific location
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-`instagram_get_nearby_locations` — Nearby location IDs (for use in location-posts)
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### Coming soon
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- TikTok (videos, profiles, hashtags)
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- X / Twitter (tweets, profiles, search)
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- LinkedIn (company pages, posts, employees)
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- YouTube (videos, channels, comments)
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Track the platform roadmap at [socialapis.io/api-sources](https://socialapis.io/api-sources).
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---
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## 💡 Usage Examples
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## 💡 Usage examples
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### Brand Monitoring
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```
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Monitor Nike's Facebook page and alert me if engagement drops below average
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```
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Each prompt below is a real Claude Desktop session. Some of these are single-tool-call patterns ("get me X"); some require Claude to chain multiple calls + aggregate the results (noted where).
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### Competitive Analysis
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```
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Compare engagement rates between Nike, Adidas, and Puma over the last month
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```
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### Single-call patterns (fast, cheap)
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### Content Strategy
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```
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What types of posts get the most engagement on Coca-Cola's Facebook page?
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What's Nike's follower count on Facebook?
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→ Uses facebook_get_page_details (1 credit)
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Get the latest 9 posts from facebook.com/EngenSA
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→ Uses facebook_get_page_posts with limit=9 (1-3 credits depending on actual returned count)
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Show me the Meta ads currently running for "Apple Vision Pro" in Germany
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→ Uses facebook_ads_search (1 credit)
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```
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### Sentiment Analysis
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### Multi-call patterns (Claude orchestrates these — but it's slower + more expensive)
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```
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Analyze comments on our recent posts and identify common themes
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Compare engagement on Nike vs Adidas's last 9 Facebook posts
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→ Claude calls facebook_get_page_posts twice (~2-6 credits total),
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aggregates reactions/comments/shares per post, returns a comparison.
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What are people saying in the comments on Coca-Cola's last 3 posts?
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→ Claude calls facebook_get_page_posts (1 credit) then
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facebook_get_post_comments 3 times (3 credits) and summarizes.
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Show me marketplace listings for "PlayStation 5" under $400 in Berlin
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→ Claude calls facebook_marketplace_city_coordinates (1 credit) +
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facebook_marketplace_search with filters (1 credit).
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```
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### What this MCP server does NOT do
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Some queries look natural in a chat ("compare engagement over the last month") but require aggregations the API doesn't expose as a single tool yet. Claude can still answer them, but it'll fan out into many tool calls — which is slow + expensive.
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| Query shape | Why it's hard |
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|---|---|
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| "Engagement rate over the last 30 days" for a page | Requires fetching every post in the date range (paginated, `limit` capped at 9 per call) and computing engagement per post. Hits the LLM tool-call budget on busy pages. |
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| "Compare engagement rates between Brand A, B, C over the last month" | Same problem, 3× — one paginated fetch per brand, then comparison math. Works for small windows; slow for "last month" on high-volume pages. |
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| Historical archive older than what Facebook itself serves | We surface what Facebook makes publicly visible. Posts that scrolled off Facebook's visible feed aren't retrievable. |
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| Server-side time-series (daily engagement, weekly growth) | Not yet — on the roadmap as a future `engagement-stats` endpoint with built-in aggregation. |
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If your use case maps to one of these patterns and you want the aggregation pre-computed instead of LLM-orchestrated, [contact support](https://socialapis.io/contact-us) with the specific query — we're prioritizing the aggregation endpoint based on customer demand.
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