📅 2025-04-22 — Session: Architected AI Agent Systems with MCP Integration
🕒 00:50–01:45
🏷️ Labels: Ai Agents, Mcp Integration, Agent Architecture, Ai Operations
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to explore and architect AI agent systems using a structured approach, focusing on integration with the Model Context Protocol (MCP) and other tools.
Key Activities
- Layered Execution Model: Defined a three-layered architecture for agent systems, emphasizing modularity and observability.
- Chief of Flows Concept: Explored a creative narrative for AI operations roles.
- Mission Management Structure: Developed a framework for managing AI-driven objectives through a
/missions/directory. - MCP Integration: Discussed integrating MCP with VS Code, Chrome, and Microsoft’s PromptFlow, outlining strategies and schemas.
- AI Orchestration Platforms: Reviewed alternatives to Microsoft PromptFlow, including LangChain and Orq.ai.
- AI Company Structure: Proposed a modular mission-driven structure for AI companies.
- Embedding System Design: Designed a 2025-ready embedding system for AI architecture optimization.
Achievements
- Established a comprehensive framework for architecting AI agent systems.
- Clarified integration strategies for MCP with various platforms and tools.
- Outlined innovative concepts for AI operations and company structure.
Pending Tasks
- Further exploration of MCP integration with additional platforms.
- Implementation of the proposed AI agent architecture and embedding system design.