Case / ManagedCode.MCPGateway
When the tool list outgrows the chat
When a product has hundreds or thousands of things it can do, handing the AI every one of them stops working.
- Works in
- ChatGPT
- Claude
- Gemini
- Coding agents
Pressure01
More tools create a discovery problem.
A long list of tools eats up the conversation and makes the AI's choice harder, not easier. Our layer registers everything the product can do, then finds the small relevant set for each request.
Mechanism02
Search first. Run second.
The AI chat searches a catalog, then runs the one action it picked through a single execution path. Your application still owns how it is deployed and how it scales.
Registry · local tools and remote MCP servers
crm.update_record
Localcalendar.book_slot
Remote MCPnotify.customer
Remote MCPOnly the capabilities you choose are passed downstream.
Proof03
The code is public.
ManagedCode.MCPGateway targets .NET 10 and uses the official MCP C# SDK. Read the contracts, the examples, and the current limits in the repository.
Where this comes from.04
Straight from the official OpenAI and Model Context Protocol documentation.
ManagedCode.MCPGateway
Public repository for the Managed Code MCP Gateway implementation and its current contracts.
02Model Context Protocol · tools specification
Protocol reference for named, discoverable tools and their input and output contracts.
03OpenAI · Apps SDK
Official guide to MCP servers, tools, authentication, and UI for ChatGPT apps.
AI / Second opinion05
Not sure where to start? Ask an AI.
Paste this question into ChatGPT, Claude, or Gemini. It walks you through finding the one task your customers would most want to finish by chatting, instead of clicking through your app.
“I run a software product. Help me identify one high-value workflow my customers could finish inside ChatGPT instead of switching between tabs. Ask me about the product, the user, the action, the data it needs, permissions, and the safest small first release.”
The prompt is copied as a backup. Some AI chats may ask you to paste it after sign-in.
FAQ06
Questions, answered.
Is this just an MCP server?
No. The server is one piece. We do the whole job: we pick the customer task, set who can do what, handle the quirks of each AI chat, make the actions run fast, add monitoring, test it, and ship it.
Do we have to rebuild our product?
Almost never. Our layer sits in front of what your product already does. We start with one small workflow and grow from what works.
Will it work in ChatGPT, Claude, and Gemini?
The same build can serve all three. Each one has its own sign-in, look, approval step, and publishing rules, so we set up and test each one separately.
How do you keep it safe?
Your product decides what is allowed, and we keep that in charge. Every action is spelled out, every input is checked, and the customer sees an approval step before anything happens. Our layer sits beside your product, not inside it.
Where does it run? Does it touch our code?
It runs as a separate service in front of your product. It never goes into your code, and you still own your data.
What does it cost, and how fast?
A first workflow starts at €3,200 and goes live in about 7 days.
Contact us07
Now build yours
Send us your product, who uses it, and the action you have in mind. We will tell you the smallest version worth building, and whether it is a €3,200 first workflow or something that needs a closer look first.