You will get your REST API into an MCP Server for Claude and AI Agents
Project details
Your API already works. The problem is letting an AI agent call it without handing over your keys, and without the agent touching something it should not.
I turn your REST API into an MCP server. MCP is the protocol Claude and other agents use to call outside tools. You send the OpenAPI spec, you get a server your agent can connect to.
The model never sees your credentials. Auth stays on the server side. Operations that change data are blocked until you turn them on, one at a time.
I have 15 years as a .NET engineer, mostly in banking and travel tech, where code has to survive audits and production load.
The gateway behind this service is public: github.com/guimvolpe-droid/openapi-mcp, written in C# on .NET 8, with 30 automated tests and green CI. Read the code
I turn your REST API into an MCP server. MCP is the protocol Claude and other agents use to call outside tools. You send the OpenAPI spec, you get a server your agent can connect to.
The model never sees your credentials. Auth stays on the server side. Operations that change data are blocked until you turn them on, one at a time.
I have 15 years as a .NET engineer, mostly in banking and travel tech, where code has to survive audits and production load.
The gateway behind this service is public: github.com/guimvolpe-droid/openapi-mcp, written in C# on .NET 8, with 30 automated tests and green CI. Read the code
AI Algorithms
Large Language Model, Transformer ModelAI Applications
Conversational AIAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$149
|
Standard
$349
|
Advanced
$699
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 12 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 |
Frequently asked questions
About Guilherme
AI Integration Engineer | .NET, Java, Python, Node.js | RAG, LLMs
Araraquara, Brazil - 10:33 am local time
Most AI projects fail at the integration layer, not at the model. That is the part I do well.
What I build:
- AI features inside the system you already run, not standalone demos
- MCP servers that let AI agents call your existing APIs behind a policy gate
- RAG chatbots that cite sources and refuse when the content does not cover the question
- API integrations with retries, idempotency and clear error contracts
Proof, not claims:
- Four public repos on my GitHub, all with green CI
- 82 automated tests across them
- One repo turns an OpenAPI spec into an MCP server with a policy gate in front of every call
- Two of the four are TypeScript on Cloudflare Workers, the other two are C# and Angular
How I work:
- Fixed price milestones, so you see value early
- Clear scope and honest estimates. If a job takes two days I will not quote ten
- Tests and documentation by default
Tell me which system the AI needs to live in and what it is written in. I will tell you how I would wire it.
Steps for completing your project
After purchasing the project, send requirements so Guilherme can start the project.
Delivery time starts when Guilherme receives requirements from you.
Guilherme works on your project following the steps below.
Revisions may occur after the delivery date.
Confirm the operation list
I read your spec or docs and come back with the exact list of operations the agent will be able to call. You approve that list before I write anything, because it is your security policy, not mine.
Generate the server
Every approved operation becomes an MCP tool with a typed input schema. Auth is wired on the server side, so the key is attached to the outbound request and never enters the model's context.