Service

MCP Servers

Give your AI model a direct line to your systems. MCP is the protocol. I build the server.

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What this covers

Custom MCP server development

Purpose-built MCP servers that expose your internal systems as tools Claude can call. Inventory, fulfilment, CRM, billing — anything with an API.

Tool schema design

Well-defined tool schemas that give the model exactly the right interface — specific enough to be reliable, flexible enough to handle real-world variation.

Stdio and HTTP transports

MCP servers that run locally over stdio or serve remotely over HTTP. Deployed in Docker, integrated with your existing infrastructure.

Open source publication

If the use case is generic enough to help others, I can package and publish the server publicly — like Swell MCP, available on GitHub.

How it works

01

Map the system surface

We identify which operations, data sources, and workflows the model needs to reach. Then we design the smallest set of tools that covers it completely.

02

Build the server

MCP server implementation with proper error handling, auth, and input validation. Tools that fail gracefully tell the model what went wrong — not just that it did.

03

Integrate and test

Connected to your AI client or agent loop. Tested against real queries until the model uses the tools correctly and consistently.

In the wild

$ mcp.server.start('eva')

> Registering tools...

> Server listening on stdio

Eva MCP

MCP server

Production MCP server for Eva — a mini ERP covering inventory, fulfilment, and warehouse management. Live in market.

$ mcp.server.start('swell')

> Loading ecommerce tools...

> Published to GitHub

Swell MCP ↗Open source

Open source MCP server for the Swell ecommerce platform. Published on GitHub for the community.

Your systems. Your model.
Connected properly.

Tell me what your AI needs to reach and I'll build the server that gets it there.

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