Web Development
AI Integration for Your App: Chatbots, RAG and MCP Servers
- From $399
- 7-day delivery
- 3 revisions
- Secure checkout

I add useful AI to your product, not a demo: a support chatbot that answers from your own docs, smart search, document processing, or an MCP server that lets Claude, ChatGPT and Cursor use your product's data and actions safely.
What's included
- Use case review: where AI saves time and where it does not
- Chatbot or assistant over your docs and database (RAG)
- Integrations with Claude, OpenAI, Gemini or self-hosted models
- MCP server in TypeScript exposing your app's tools and data
- Auth, rate limits and cost controls so usage cannot run away
- Logging and evaluation so you can see answer quality
Who this is for
- SaaS products adding AI features
- Support teams answering the same questions every day
- Developer tools that want to work inside AI coding agents
What I need from you
- Access to your app or API
- Example questions or tasks the AI should handle
How it works
- Message me with what you need. The first consultation is free.
- I confirm the scope and a fixed price before any work starts.
- I do the work and keep you updated in the chat.
- You review it, and I hand over notes, access and anything I changed.
Free guides on this topic
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Questions
Which AI provider is best?
It depends on the task, price and privacy needs. I test two or three on your real data and show you the results before we pick.
What is an MCP server?
Model Context Protocol is the standard way AI assistants like Claude and ChatGPT call external tools. An MCP server lets them use your product directly.
What you'll get
- Production-ready implementation tailored to your goals
- Clean, maintainable code following modern best practices
- Deployment to secure infrastructure with monitoring
- Handover with documentation and full access
Tech stack & tooling
- Frontend: Next.js, React, TypeScript, Tailwind CSS
- Backend: Node.js, NestJS, Express, REST APIs
- Database: PostgreSQL, MongoDB, Prisma
- Deployment: Docker, AWS, CI/CD
How we'll work together
We start with a short requirements discussion, agree on scope and milestones, then move through implementation, review and handover. You get clear visibility into progress and a stable deployment at the end.


