MCP Development

Give Claude and other AI assistants secure, structured access to your actual systems.

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In short

MCP (Model Context Protocol) is an open standard for connecting AI assistants to external tools and data sources through a common, structured interface, instead of a custom integration per assistant. DuCodes builds MCP servers that expose a business's internal tools, documents, or APIs to AI assistants like Claude in a secure, scoped way.

AI assistants are far more useful when they can actually reach your data and tools — your internal docs, your database, your ticketing system — instead of only working with what's typed into a chat window. MCP standardizes how that connection happens, so an AI assistant can discover and call your tools through a common protocol instead of requiring a bespoke integration for every assistant it's used with.

We build MCP servers that expose exactly the tools and data you want an AI assistant to access — read-only lookups, scoped write actions, or both — with the same care around permissions and guardrails we apply to any AI agent work.

Why work with DuCodes on this

Scoped access by design

An MCP server we build exposes only the specific tools and data you've chosen to make available — not blanket access to your systems.

Standard-based, not a one-off integration

Building to the MCP spec means the same server works with any MCP-compatible AI assistant, not just one vendor's product.

Real authentication and audit logging

Every call an AI assistant makes through your MCP server is authenticated and logged, so you know what was accessed and when.

Practical about what to expose

We'll help you decide which internal tools are actually useful to expose to an AI assistant, rather than wiring up everything by default.

How we work

1

Identify the use case

What should an AI assistant actually be able to look up or do in your systems, and for whom?

2

Define tools and scope

Which internal APIs, documents, or actions get exposed, and what permissions gate each one.

3

Build the MCP server

Implementing the protocol's tool and resource interfaces against your actual backend.

4

Secure & test

Authentication, rate limiting, and testing against both expected and adversarial usage.

5

Deploy & monitor

Logging and monitoring so you can see exactly what's being accessed through the server after launch.

Technology we use

Model Context Protocol (MCP) Python / Node.js OAuth / API key authentication Existing internal APIs Claude / MCP-compatible clients

Frequently asked questions

Whatever you choose to expose — looking up records, searching internal documents, or taking scoped actions like creating a ticket. It's entirely defined by which tools you build into the server.

Yes, when scoped correctly — we build authentication, permission scoping, and audit logging in from the start rather than exposing broad access for convenience.

MCP is an open protocol, so a server built to spec can work with any MCP-compatible AI assistant, though Claude's adoption of MCP is currently the most common use case we build for.

A regular API is built for your own application to call; an MCP server is built specifically so an AI assistant can discover and use your tools in a structured, standardized way during a conversation.

Ready to talk about your project?

Let's discuss mcp development