How It Works
Transform engagement data into predictive insights using AI-powered synthetic personas
The Pipeline
- LinkedIn profiles + activity
- Twitter/X profiles + posts
- Auto-scraped via API
- Upload subscriber list
- Subject + open/click data
- JSON format
"This user clicks on automation content but ignores strategic analysis. They prefer practical tutorials over theory. Engagement peaks with AI/ML topics."
"I'd choose [A] - practical tools are more actionable than theory"
"[A] has code examples which I need for implementation"
Why "Synthetic" Personas?
Traditional personas are fictional. These are data-grounded - they mirror real user behavior from actual engagement data.
How It Predicts Behavior
The AI learns from past engagement patterns (clicks vs impressions) to predict future content preferences.
Use Cases
Ad Testing
Test headline variations before spending on campaigns
Email Subject Lines
Upload subscriber history, predict which subject lines drive opens
Content Strategy
Validate content ideas before production
Expose this API as tools for AI agents using the Model Context Protocol.
Server Config
{
"mcpServers": {
"synthetic-personas": {
"command": "python",
"args": ["-m", "src.mcp_server"],
"cwd": "/path/to/project"
}
}
}
Available Tools
scrape_profiles
Scrape LinkedIn/Twitter URLs
generate_personas
Create personas from profiles
query_personas
A/B test content options