You will get a production-ready MCP server deployed and hardened for your team
Project details
Most MCP servers built from tutorials get you to "hello world."
Production is a different job: OAuth or SSO, per-tool access control, audit logs, rate limiting, secrets management, TLS, monitoring, and a runbook your on-call engineer can actually use.
I deploy MCP servers the way a 25+ year infrastructure engineer deploys anything else — secured, observable, documented. Recent background: four years operating GCP and Kubernetes for AI SaaS platforms, including a Meta WhatsApp partner serving billions of messages.
What you get: a working MCP server connecting your systems to Claude, Cursor, ChatGPT, or any MCP-compatible client; proper authentication (API keys in Tier 1, OAuth/SSO in Tier 2+); per-tool ACLs and rate limits; structured audit logging; Docker deployment with TLS, backups, and monitoring; and a written runbook covering deploy, restart, credential rotation, and disaster recovery.
Every engagement ends with documentation, a runbook, and a clean handoff. Not a permanent Slack channel.
Not included: writing the AI agents that consume the server, hosting the LLM, or compliance audits. Ongoing operations available as a separate monthly retainer.
Production is a different job: OAuth or SSO, per-tool access control, audit logs, rate limiting, secrets management, TLS, monitoring, and a runbook your on-call engineer can actually use.
I deploy MCP servers the way a 25+ year infrastructure engineer deploys anything else — secured, observable, documented. Recent background: four years operating GCP and Kubernetes for AI SaaS platforms, including a Meta WhatsApp partner serving billions of messages.
What you get: a working MCP server connecting your systems to Claude, Cursor, ChatGPT, or any MCP-compatible client; proper authentication (API keys in Tier 1, OAuth/SSO in Tier 2+); per-tool ACLs and rate limits; structured audit logging; Docker deployment with TLS, backups, and monitoring; and a written runbook covering deploy, restart, credential rotation, and disaster recovery.
Every engagement ends with documentation, a runbook, and a clean handoff. Not a permanent Slack channel.
Not included: writing the AI agents that consume the server, hosting the LLM, or compliance audits. Ongoing operations available as a separate monthly retainer.
AI Development Type
Knowledge Representation, Software MaintenanceAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$1,750
|
Standard
$5,500
|
Advanced
$13,500
|
|---|---|---|---|
| Delivery Time | 7 days | 21 days | 42 days |
Number of Revisions | 2 | 3 | 4 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | - | - | - |
Model Documentation | - | - | - |
Ontology | - | - | - |
Source Code | |||
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$400 - $2,500
Additional Revision
+$250
7-day post-launch priority support
(+ 7 Days)
+$650
Additional MCP server integration
(+ 7 Days)
+$1,200
Team training workshop (2 hours)
(+ 3 Days)
+$450Frequently asked questions
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JG
John G.
Oct 5, 2017
CDN, Cloudflare and Akamai Expert Needed. Looking for an expert to configure server for ecommerce website
Alexandru is an excelled System Admin. The best we've had. Everything from his skills, availability and communication have been excellent. We've needed him to fix some emergency disasters with our high end servers and he was available instantly to not only fix the problem quickly but then completely structured us a new set up the following days. This project was such a huge success. Looking forward to future work with Alex.
AM
Alan M.
Sep 22, 2017
Linux Management
Had issues with my MySQL Server having high load which Alex solved, recommended!
SF
Sam F.
Jun 28, 2017
Setup end user Self Service Password Portal with Complete Documentation.
Excellent!!
took care of Project in A timely manner
took care of Project in A timely manner
About Alexandru
Production AI Agent Infrastructure | MCP, Self-Hosted LLMs, 25 yrs Ops
100%
Job Success
Montreal, Canada - 7:25 pm local time
I close that gap.
For 25+ years I've built and operated production infrastructure — Linux and Unix systems, enterprise networks (Cisco, firewalls, segmentation), cloud environments across AWS, GCP, and Azure, virtualization on VMware and Proxmox, DevOps and CI/CD pipelines, and the on-prem and hybrid data center work that most real businesses still depend on. Most recently, I spent nearly four years operating GCP and Kubernetes infrastructure for two AI/ML SaaS platforms — one serving billions of messages to 50,000+ businesses as an official Meta WhatsApp partner, and one powering real-time AI search and recommendations for e-commerce.
I now focus that experience on deploying agentic AI systems the way real production systems get deployed: secured, observable, documented, and built to survive a Tuesday morning outage.
What I do:
MCP (Model Context Protocol) servers — design, deployment, and hardening. Connecting Claude, ChatGPT, Cursor, and other AI clients to internal systems with OAuth/SSO, per-tool access control, audit logging, and rate limiting done properly. I also handle MCP gateway setup for multi-agent or multi-user environments.
Self-hosted AI stacks — for clients with data-residency, privacy, or compliance constraints who can't send sensitive data to third-party providers. Typical stack: Ollama or vLLM for inference, OpenWebUI as the frontend, Qdrant for vectors, Langfuse for observability, behind Caddy or Traefik with HashiCorp Vault for secrets. Law firms, healthcare, finance, and GDPR-scoped organizations are the common buyers.
Hardening and rescue engagements — for existing LangChain, n8n, LlamaIndex, or CrewAI deployments that went to production before they were ready. I audit the setup, fix the top issues, and hand you a runbook so it stops breaking at 3 AM.
Team enablement — Claude Code, Cursor, and Windsurf configured properly for development teams. MCP configuration, sandbox boundaries, cost controls, and governance documentation security teams can actually sign off on.
Architecture review — for organizations evaluating or scaling agentic AI. Short, fixed-scope engagements that produce a written assessment and remediation plan.
How I work:
Fixed-price when the scope is clear, hourly when it's not. Every engagement ends with documentation, a runbook, and a clean handoff — not a Slack channel where you ask me questions forever. If ongoing operations make sense, I offer retainers separately.
Available globally (I work in English, French, Romanian, and Russian). Comfortable with clients in regulated industries — I've operated production infrastructure under GDPR, financial-markets, and multi-tenant compliance constraints.
If you're looking for someone who will build a flashy demo, I'm not your person. If you want someone who will deploy AI systems that actually work in production and hand them back to you clean, let's talk.
Steps for completing your project
After purchasing the project, send requirements so Alexandru can start the project.
Delivery time starts when Alexandru receives requirements from you.
Alexandru works on your project following the steps below.
Revisions may occur after the delivery date.
Scoping call and technical review
30-minute call to walk through your requirements, existing infrastructure, authentication needs, and compliance constraints. I'll confirm scope, flag anything that needs to change from the standard tier, and align on delivery timeline.
Architecture design and implementation plan
I design the MCP server architecture — transport, authentication, tool schema, and integration points — and share a written implementation plan. You review and approve before any code is written.