postforged-analytics-mcp
v0.1.0
Published
MCP server for LinkedIn post analytics — score content quality, predict engagement, analyze posting patterns, benchmark performance, and optimize content strategy
Maintainers
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postforged-analytics-mcp
LinkedIn post analytics MCP server — score content quality, predict engagement, analyze posting patterns, benchmark performance, and optimize content strategy.
Tools
| Tool | Description |
|------|-------------|
| score_post_quality | Score a LinkedIn post for readability, hook strength, CTA effectiveness, and overall engagement potential |
| predict_engagement | Predict likes, comments, shares, and impressions based on content and audience |
| analyze_posting_pattern | Analyze posting frequency, timing, and content mix for optimization |
| benchmark_performance | Compare your performance against industry benchmarks by audience size |
| optimize_content_strategy | Generate a data-driven content calendar and growth strategy |
Installation
npx postforged-analytics-mcpConfiguration
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"postforged-analytics": {
"command": "npx",
"args": ["-y", "postforged-analytics-mcp"]
}
}
}Environment Variables (Optional)
POSTFORGED_API_URL=https://postforged.com
POSTFORGED_API_KEY=your-api-keyExamples
Score a Post
Use the score_post_quality tool to analyze:
"Stop writing LinkedIn posts about being excited to announce things.
Nobody cares about your announcement. They care about what's in it for them.
Here's what top 1% of LinkedIn creators do instead:
1. Lead with a contrarian take
2. Share specific numbers
3. End with a question
What's the worst LinkedIn opener you've seen?"Predict Engagement
Use predict_engagement with followerCount: 5000, format: "carousel", industry: "tech"License
MIT — postforged.com
