The Model Context Protocol is how AI models like Claude connect to the real world — your databases, your APIs, your internal tools. We build the servers that make that connection production-ready, secure, and actually useful.
The Model Context Protocol (MCP) is an open standard introduced by Anthropic that defines how AI models communicate with external data sources and tools. Think of it as a universal adapter — instead of building a custom integration for every AI model and every data source, you build one MCP server and any compatible AI can use it.
Before MCP, connecting an AI model to your internal systems meant custom code for every combination: one integration for Claude + your CRM, another for Claude + your database, another for GPT + your CRM, and so on. It didn't scale, and every integration broke independently.
With MCP, you build the server once. The server exposes your data and tools through a standardized interface. Any MCP-compatible AI model — Claude, and increasingly others — can connect to it and use your data in real time, with proper authentication and access controls.
This is early-stage infrastructure, which means the companies building MCP capability now will have a meaningful head start. We're already building production MCP servers.
MCP isn't replacing REST APIs — it's a layer on top of them, purpose-built for AI interactions.
| Capability | Traditional API Integration | MCP Server |
|---|---|---|
| AI model compatibility | One integration per model | Any MCP-compatible model |
| Tool discovery | Hardcoded, manual | Dynamic, AI-readable descriptions |
| Context passing | Custom per implementation | Standardized protocol |
| Auth & security | Varies wildly | OAuth 2.0 built into spec |
| Maintenance overhead | High — breaks with every model update | Low — protocol handles abstraction |
| Multi-tool orchestration | Complex custom logic | Native to the protocol |
Every MCP server we deliver is production-grade — authenticated, logged, tested, and deployable in your existing infrastructure.
Give AI models read (or write) access to your PostgreSQL, SQL Server, or MySQL databases through a controlled, authenticated interface. The AI can query your data in real time without you exposing raw database credentials.
Wrap your existing internal APIs — CRMs, ERPs, inventory systems, order management — in an MCP interface so AI models can call them as tools. No rearchitecting your existing systems required.
MCP servers that expose your document stores, SharePoint libraries, S3 buckets, or knowledge bases to AI models — with chunking, search, and retrieval built in.
MCP servers with full OAuth 2.0 / OIDC authentication, role-based access controls, audit logging, and rate limiting — meeting enterprise security requirements out of the box.
MCP servers that expose business actions — create a ticket, send a notification, update a record, trigger a workflow — so AI agents can take real actions in your systems, not just read from them.
A single MCP server that aggregates data from multiple sources — pulling from your database, your API, and your document store in a single tool call — simplifying the AI's job and reducing round trips.
We map the data sources and actions the AI needs access to, define the tool interface (what inputs the AI sends, what outputs it gets back), and establish security boundaries — what the AI can and cannot do.
We implement OAuth 2.0 or OIDC authentication, map access scopes to your existing user roles, and set up audit logging so every AI action is traceable. Enterprise security is not an afterthought.
We build the MCP server using the official SDK, write the tool handlers, connect to your data sources, and run it against real AI model interactions — not just unit tests — to verify behavior under actual conditions.
We deploy to your infrastructure (AWS, Azure, or on-prem), configure your AI model to use the server, and verify the end-to-end flow. We document the server thoroughly so your team can extend it.
15 minutes, no obligations. Tell us what systems you want to expose and we'll tell you honestly what it would take to build it production-ready.
Book a Discovery Call