I build the systems between the tools a business already uses: reliable data pipelines, AI agents, and the infrastructure that keeps both running.
I am the co-founder of WhiteCap Data, where I help small and midsize businesses connect fragmented systems and replace manual handoffs with dependable automation.
My work sits at the intersection of:
- Data integration: CRM, billing, communications, spreadsheets, and operational systems connected around a trustworthy source of truth.
- AI and agent engineering: MCP tooling, local and hosted LLM workflows, voice agents, evaluation, and production automation.
- Infrastructure: Linux, Docker, Kubernetes, Cloudflare, private networking, monitoring, backups, and incident recovery.
I prefer practical systems that are observable, recoverable, and useful to the people operating them.
| Project | What it does | Install |
|---|---|---|
| MCPGauge | Deterministic, offline quality grading for MCP servers. | pip install mcpgauge |
| Ollama Handoff | Sends suitable agent tasks to a local Ollama model to reduce cloud cost. | pip install ollama-handoff |
| TableBridge | Read-only, sandboxed SQL over folders of CSV, Parquet, and JSON files using DuckDB. | pip install tablebridge |
| WhiteCapData Dev | MCP tools for operating Kubernetes and k3s environments with safe defaults. | pip install whitecapdata-dev |
| Finance Tracker | Local-first subscription, budget, alert, and overdraft forecasting software. | Self-hosted |
All four Python tools above are available on PyPI and developed in public.
I contribute fixes, tests, and documentation upstream across Python, DuckDB, Model Context Protocol, Pipecat, FastMCP, ESLint, and Ansible projects.
Recent work includes:
- DuckDB SQL documentation for
PREPARE,EXECUTE, andDEALLOCATE, merged upstream. - Rule-language metadata and configuration safety for ESLint Stylistic.
- Garbage collector documentation corrections for CPython.
- Fixes and documentation for MCP Apps, Pipecat, and FastMCP.
Languages: Python, TypeScript, JavaScript, SQL, Go
AI and data: MCP, Claude, Ollama, DuckDB, Pipecat, agent evaluation
Infrastructure: Linux, Docker, Kubernetes/k3s, Cloudflare, Supabase, Tailscale, OPNsense
Current systems: a five-node self-hosted k3s environment, production agent workflows, voice automation, and data-integration pipelines for business operations.
I am open to data-integration projects, AI and agent build-outs, workflow automation, and practical infrastructure work for small businesses.
Michael Tierney · Finger Lakes, New York