You will get I will build a custom MCP (Model Context Protocol) server for Claude
Project details
Your team already has the data. It lives in your internal API, your database, your admin panel - and every question about it costs someone twenty minutes of clicking
An MCP (Model Context Protocol) server puts that data one question away. Your team asks Claude in plain English, Claude queries your real system, and the answer comes back grounded in real data instead of guessed.
WHAT YOU GET
• A working MCP server connected to your tool, database, or API
• Clean tool definitions so Claude knows when to use each one
• Setup instructions for whoever maintains it after me
HOW I BUILD IT
Read-only by default. Every query parameterised. Results capped, so a model asking for everything does not pull your whole table into a context window. Errors come back readable instead of failing silently.
WHY ME
8 years keeping production systems running, most recently as an AKS Escalation Engineer at Microsoft. An MCP server is infrastructure, and most of the work is what only shows up when something breaks: auth, rate limits, timeouts, permissions, bad input.
Tell me what your team keeps looking up and I will say honestly whether this is the right fix.
An MCP (Model Context Protocol) server puts that data one question away. Your team asks Claude in plain English, Claude queries your real system, and the answer comes back grounded in real data instead of guessed.
WHAT YOU GET
• A working MCP server connected to your tool, database, or API
• Clean tool definitions so Claude knows when to use each one
• Setup instructions for whoever maintains it after me
HOW I BUILD IT
Read-only by default. Every query parameterised. Results capped, so a model asking for everything does not pull your whole table into a context window. Errors come back readable instead of failing silently.
WHY ME
8 years keeping production systems running, most recently as an AKS Escalation Engineer at Microsoft. An MCP server is infrastructure, and most of the work is what only shows up when something breaks: auth, rate limits, timeouts, permissions, bad input.
Tell me what your team keeps looking up and I will say honestly whether this is the right fix.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI-Generated Code, AIOps, Conversational AI, Natural Language UnderstandingAI Development Language
PythonAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$200
|
Standard
$650
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 5 days | 8 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | |||
Detailed Code Comments | |||
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | - | |
Model Documentation | - | ||
Model Monitoring | - | - | |
Model Testing & Optimization | - | ||
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | |||
Source Code |
Optional add-ons
You can add these on the next page.
Additional Revision
+$75
Extra Tool
(+ 2 Days)
+$120Frequently asked questions
About Bryan
AI Automation for Ops Teams | n8n - MCP - Claude API - Ex-Microsoft
San Pedro, Costa Rica - 12:40 pm local time
I spent 8 years keeping production systems alive — most recently as an Azure Kubernetes Escalation Engineer at Microsoft, where my job was diagnosing the failures nobody else could. CKA certified (Linux Foundation, 2022). I now build AI automation on top of that operational background, which means I understand the systems I am automating, not just the API I am calling.
What I build:
· Custom MCP servers so your team can query internal tools directly from Claude
· n8n workflows with Claude or GPT in the loop — alert triage, ticket routing, report generation
· Claude API integrations into the tools you already run
· Google Workspace automation that actually handles edge cases and rate limits
Recent work is public on GitHub under br-suarez, including a working MCP server with full documentation and a Kubernetes lab portfolio.
Based in Costa Rica, working US hours (CST). Fluent English and Spanish.
Tell me the process that is eating your team's time and I will tell you honestly whether automating it is worth it.
Steps for completing your project
After purchasing the project, send requirements so Bryan can start the project.
Delivery time starts when Bryan receives requirements from you.
Bryan works on your project following the steps below.
Revisions may occur after the delivery date.
Scope call and tool design
We go through the questions your team asks manually and turn them into a concrete tool list. You approve that list before I write any code, so the scope is fixed in writing.
Build against your data model
I implement the tools against sandbox or read-only credentials. Parameterised queries, capped results, readable errors. Nothing touches production.