Linux / DevOps engineer | Amateur Radio & Big Data enthusiast | Exploring AI Agent (MCP) integrations
I’m a long-time Linux user (since the Slackware days) and active supporter of Open Source Software.
- Ubuntu user since 2005 (5.04), Ubuntu Member since ~2013
- Launchpad Package Maintainer since 2010
- Daily driver: Ubuntu & Oracle Linux (enterprise), Pop!_OS for gaming, Alpine for containers
I’ve worked across Red Hat, Fedora, CentOS, Arch, Gentoo, and more. In short: if it’s Unix-y, I’ve probably used it.
- Infrastructure as Code → Terraform & Ansible with OCI, Nomad, Docker/LXC
- Distributed Systems → Vault, Consul, HA setups
- Big Data in Amateur Radio
- wspr-ai-lite — lightweight DuckDB + Streamlit UI with MCP agent support
- WSPR Analytics (Scala, PySpark, Apache Arrow)
I’m actively building Model Context Protocol (MCP)-enabled backends for amateur radio analytics:
- wspr-ai-lite → first MCP-ready WSPR dataset explorer
- Safe, contract-driven database queries exposed to AI Agents
- Roadmap includes ClickHouse, FastAPI/Uvicorn, and agent-driven analytics for propagation research
This bridges amateur radio + AI workflows, enabling safe automation and intelligent query interfaces.
- 2x 16-Core virtualization nodes ( AMD x5950 )
- 2× 4-core virtualization nodes ( AMD V1605B SoCs )
- 1x 48TB TrueNAS Storage Server
- Proxmox hypervisor with clustered VMs/containers
- Dual-WAN via pfSense + Netgate 3100
- Networking: USW-PRO-24 PoE, US-XG-16 aggregation, TrueNAS ZFS storage
- Lab for container orchestration, monitoring, and WSPR data crunching
- WSPR Analytics → Big Data exploration of WSPR spots
- wspr-ai-lite → portable DuckDB + Streamlit with MCP integration
- Open for discussions on Linux, DevOps, Amateur Radio, or AI Agents
- Reach me on GitHub Discussions

