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Česky
Running apps and systems with no AI connector? We'll build an MCP gateway over any existing API, database, or application of yours. Copilot, Claude, ChatGPT, and any other MCP-compatible agent then gets clean, authenticated, audit-logged access to the target systems. No copy-paste. No screen scraping. No prompt-engineered duct tape.
Start a projectMCP is the open standard that lets an agent call your APIs the way any application would — with defined tools, structured arguments, and real auth. We deliver MCP servers over ERPs, CRMs, ticket systems, SQL warehouses, and proprietary back-offices. Same pattern every time: your data, your perimeter, the agent of your choice.
Open a ticket for the failed deploy and assign it to whoever shipped the last release.
Build a report of how many hours each person on my team logged on individual projects last month.
What sales activities happened last week, and where's my next scheduled follow-up?
Turn any REST, GraphQL, or SOAP API into a clean MCP server with typed tools agents can discover and call.
Entra ID, OAuth, OIDC, API keys, mTLS — agents inherit the user's permissions, not a service account's.
Tool schemas can be generated from Swagger/OpenAPI. We'll then propose optimizations that improve usability and efficiency.
Direct SQL/NoSQL access with optional read-only mode, query budgets, and PII redaction.
Whether aggregated or every single tool call and response — captured, queryable, and pipe-able to your SIEM.
Your MCP server runs on our side (Azure) — nothing for you to worry about. Have your own Azure, Google Cloud, AWS, or on-premise servers? Running from your environment is a given.
Most "AI integration" projects in 2026 are still uploading documents and asking questions. That's a useful starting point. It's not where the value is.
The value is when an agent can act — open a ticket, post a transaction, log timesheets, refund a customer — through the same auth and audit machinery your humans use. To make that happen, agents need tools. And that's MCP.
We start with a kickoff meeting: what systems, what data, what permissions, what's the agent supposed to actually do. Then a one-to-five-day (!) build of the MCP server and registration with the AI platforms, where you can try everything immediately.
From there: hardening, monitoring, expanding the toolset, and — crucially — teaching your operators how to write good system prompts and read audit logs. We hand the keys over at the end.