From MCP servers to production Kubernetes
The work behind the way I build today: MCP servers that let AI assistants act on real systems behind approval gates, a memory hub that makes past sessions from several AI tools searchable by all of them, a portfolio platform with its own MCP server, a family of versioned NestJS packages extracted from production backends, a cooperative finance platform where every figure traces to a ledger entry, a booking platform and operator network running on one backend, and the move of that live platform onto self-hosted Kubernetes with no recorded downtime.
A few platforms told properly: what they are, how they are built, and what they run on. Each one links to its full case study.
Assistants forget between sessions, and each provider keeps its history in its own shape, so knowledge earned in one conversation is unavailable in the next. We built the plumbing that fixes it: MCP servers that expose knowledge, content and tools to any assistant, and a memory hub that normalises sessions from several providers into one queryable store. None of the hard problems here were prompt problems. They were system problems: schema design across incompatible session formats, isolation between scopes, tool safety, and an approval model for anything that writes. It runs on self-hosted hardware, so nothing leaves the building.

A static portfolio site could not carry work in five languages or keep pace with the writing behind it, so we replaced it with a platform. A headless CMS holds every case study, article and record; a Next.js front end renders them in English, Bengali, Spanish, Hindi and Chinese; and an MCP server exposes the same content to AI assistants, so an agent asked about this work reads the source rather than guessing from a scrape. Search, media handling, an approval flow and a public discovery layer all run on it. The proof is recursive: the page you are reading is served by the system this entry describes.

A cooperative finance organisation was running member records, savings, loans and investor capital across paper and spreadsheets, with no way to audit a branch or close a day cleanly. We built one system that holds all of it: member registration, daily collections, loan application through to disbursement, a multi-branch ledger, investor capital and an audit log that records who did what. Field officers work from a phone, managers from a desk, and the permission model decides which features each role sees rather than hiding buttons. Everything shown in this case study runs on seeded demonstration data; real member records never appear in portfolio material.

Every backend repeats itself: authentication, configuration, CRUD, file storage, background workers, PDF generation, feature flags and audit trails. We built ours once, as fourteen versioned NestJS packages under one scope, and install them into every project we ship. They are ours rather than a registry's, built for our own work, and versioned with the discipline a public library needs anyway: semantic versions, a changelog, and a packed tarball pinned per project so an upgrade is a decision rather than an accident. Library code has to answer requirements nobody has stated yet without breaking whoever depended on yesterday's answer. That constraint is why a new project starts at week three instead of week one.

Fully Booked is a booking platform for UK minibus and coach hire and the job-sharing network of operators behind it. A customer describes a trip once on the customer website and receives offers from the operators who can serve it, ranked with reviews and vehicle photos, then books with a small protected deposit. An operator who cannot take a job refers the customer from the app, and earns a share when another firm in the network carries it. Around that loop sit quotations, cancellations, Get Covered, partner contacts, stored bookings, a wallet, business pages and the Prebooked widget, all on one backend and run from an admin control room.
Jun 24, 2025



Fully Booked ran on managed cloud infrastructure with a bill that grew every month and a stack nobody fully owned. We moved the whole platform onto a self-hosted Kubernetes cluster without a minute of downtime for the people using it. The cutover covered DNS, ingress, databases and the release pipeline, staged so that traffic shifted only once each layer had been proven on the new cluster. Nobody using the app that week knew anything had happened, which was the point. The recurring bill became owned hardware, and the same cluster now carries the platform's weekly releases.
Jun 23, 2026

An MCP server sits between an AI assistant and the systems it works on, and every action that writes goes through an approval gate. The same habit runs through the rest of this work: the finance platform traces every figure to a ledger entry, the portfolio platform keeps drafts behind a review, and a live platform moved to new infrastructure with a rollback ready at every step.


Upwork publishes its own lists of the freelancers it recommends for each skill and country. In 2023 its "Top React Native Developers in Bangladesh" list put my profile first, and in 2025 its "Hire the best React Native Developers in Bangladesh" page listed it second. The rankings and their wording are Upwork's. This page keeps that record next to the React Native work behind it: apps for iOS and Android, built from the architecture and the backend through to the store release.
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