/
/
We build Model Context Protocol layers over your existing APIs, databases, and applications — giving Claude, ChatGPT, and any MCP-aware agent clean, authenticated, audit-logged access to your 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 a developer would — with typed tools, structured arguments, and real auth. We've shipped MCP layers 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 in Jira for the failed deploy and assign it to whoever shipped the last release.
Pull the contract for ACME Corp from SharePoint and summarise the renewal clauses.
Run the customer-churn query against our warehouse and chart the result.
Turn any REST, GraphQL, or SOAP API into a clean MCP server with typed tools agents can discover and call.
OAuth, OIDC, API keys, mTLS — agents inherit the user's permissions, not a service account's.
Auto-generated tool schemas from OpenAPI, GraphQL, or hand-written definitions. Agents see what's available.
Direct SQL/NoSQL access with read-only safeties, query budgets, and PII redaction at the boundary.
Every prompt, every tool call, every response — captured, queryable, and pipe-able to your SIEM.
Deployed in Azure, AWS, or your own datacentre. Monitored, scaled, SLA-backed for agent-critical paths.
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, schedule a meeting, kick off a deploy, refund a customer — through the same auth and audit machinery your humans use. That requires a real protocol. MCP is what we use.
We start with a one-week discovery: what systems, what data, what permissions, what's the agent supposed to do. Then a two-to-six-week build for the first MCP server, deployed to a staging environment your team can hammer on.
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.