Tenx MCP Setup & AI Orchestration Challenge

This repository contains my submission for the Tenx MCP Setup Challenge. The goal of this project was to establish a high-fidelity connection with the Tenx Analysis MCP server and implement an advanced AI orchestration workflow.

🚀 Key Features

• MCP Integration: Real-time interaction logging with the Tenx Feedback Analytics server.
• Orchestration Workflow: Implementation of a "Plan-Execute-Verify" cycle inspired by Boris Cherny.
• Persistent Memory: Use of an agents.md file to maintain project-specific context and standards across sessions.

🛠 Setup & Configuration

• IDE: Cursor
• Agent: Cursor AI (configured via .cursor/)
• MCP Server: Tenx Feedback Analytics

📄 Documentation

• Detailed insights and troubleshooting can be found in REPORT.md.
• Global agent rules are defined in .cursor/rules/agent.mdc.
• Project-specific standards are maintained in agents.md.
• External sources and citations: EXTERNAL_SOURCES.md.
• Rule version history: RULE_VERSION_HISTORY.md.