Content Marketing AI Engine
See 4 architectures solve real problems: MCP → RAG → Multi-Tool → Multi-Agent
Advanced Multi-Agent System
BOFU: Production LangGraph with Router → Specialized Agents → Aggregation
1. Select Analysis Scenario
2. Monday's Prompt
3. Run Multi-Agent Workflow
MCP Tool Use Pattern
TOFU: LLM calls tools via Model Context Protocol - see real tool execution
Automation Task
User query → LLM decides tool → Executes get_keyword_data() → Returns SEO metrics
Terminal ready. Run simulation to begin.
RAG-Based Content Search
MOFU: Search 100+ content pieces with vector similarity
Search Query
"Search Past Content Performance"
Embed query → Search vectors → Retrieve top-performing posts → Generate performance report
RAG Vector Search Network
Search Results
Run visualization to see results
Multi-Tool Content Orchestration
MOFU: Multiple tools working together automatically
ROI Analysis
Orchestrator calls: scraper_tool(25_competitors) → seo_tool(50_keywords) → social_tool(5_platforms) → analytics_tool(our_content) → All execute in parallel → Aggregator combines → Report generated → Alerts sent if significant changes
Time to Complete
Cost per Analysis
Data Points Analyzed
Accuracy Rate
Reports per Day
Error Rate
Ready for Production Content Marketing System?
We'll build your custom system: MCP tools (TOFU) → RAG search (MOFU) → Multi-tool (MOFU) → Multi-agent (BOFU). From demos to deployment in 8 weeks. Transform 8 hours/piece → 45 min/piece.
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