AI Engineer focused on building intelligent agent systems and Model Context Protocol (MCP) infrastructure. Based in Seattle, I'm currently working on PeakMojo, building innovative AI-powered solutions for sales training and customer success.

I'm passionate about leveraging AI technology to create practical tools that empower human-AI collaboration through standardized protocols. My work spans from backend development to AI agent architecture, with a focus on building infrastructure that connects AI models to real-world applications.

I'm currently focused on building Model Context Protocol (MCP) servers that enable AI agents to interact with various services and platforms:

• agentic-mcp-client - The first open-source standalone agent runner that executes tasks using MCP (Model Context Protocol) tools via Anthropic Claude, AWS BedRock and OpenAI APIs. It enables AI agents to run autonomously in cloud environments and interact with various systems securely.

• mcp-remote-macos-use - The first open-source MCP server that enables AI to fully control remote macOS systems through screen sharing. Allows AI agents to capture screenshots, send keyboard inputs, control mouse movements, and interact with any macOS application.

• mcp-hubspot - MCP server for HubSpot CRM integration, allowing AI models to interact with HubSpot data and operations through a standardized interface.

• mcp-headless-gmail - Headless Gmail integration through MCP, enabling AI assistants to read, search, and send emails.

• mcp-server-zoom-noauth - A MCP server for accessing Zoom recordings and transcripts without requiring direct authentication from the end user.

• my-apple-remembers - MCP server for reading and managing Apple Notes on macOS, giving AI assistants access to personal note content.

• mcp-server-any-openapi - Production-grade solution for API spec analysis that indexes and queries OpenAPI endpoints using endpoint-centric semantic search.

• mcp-server-aws-resources-python - MCP server for AWS resource management through Python's boto3, enabling AI agents to work with AWS infrastructure.

• Languages: Python, JavaScript, TypeScript
• AI & ML: Model Context Protocol (MCP), OpenAI API, Anthropic Claude
• Cloud: AWS, Docker, Kubernetes
• Containerization: Docker, buildx for multi-platform builds
• API Integration: REST APIs, OpenAPI specifications
• Remote Control: Screen sharing, keyboard/mouse automation

• Advancing AI agent capabilities through MCP infrastructure
• Building better tools for AI-human collaboration
• Cross-platform AI agent control systems
• Integrating AI with enterprise platforms and services
• Containerized solutions for AI tooling

• LinkedIn: in/baryhuang
• Website: https://peakmojo.ai
• Twitter: @buryhuang

Feel free to reach out if you're interested in collaborating on Model Context Protocol projects or want to discuss the future of AI agent infrastructure!