Direct production access
Tools and agents connect straight to production systems with no mediation layer.
AI platform engineering
The clean way to connect AI to your systems.
MCP is how you give an AI controlled access to tools and data without handing over raw credentials. We build custom MCP servers that expose exactly the operations an agent needs — read this, write that, nothing more — with authentication, scoping and logging built in. It's the difference between a governed integration and a dangerous one.
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Architecture
flowchart LR
AG[AI Agent] -->|structured request| MCP[MCP Server]
MCP --> AUTH[AuthN and Scope Check]
AUTH -->|least privilege| API1[Internal API]
AUTH --> DB[Database read-only]
MCP --> LOG[Audit Log]
AUTH -. deny out-of-scope .-> AG
Business challenges
MCP Development challenges we solve.
Every recommendation starts with business pressure, technical risk and the operating model required after launch.
Custom, unaudited connectors
One-off integrations are built without consistent access control or logging.
No least-privilege model
Any connected agent can reach more tools than its task actually requires.
Solution overview
MCP Development designed for production readiness.
We build custom MCP servers that expose exactly the operations an agent needs — read this, write that, nothing more — with authentication, scoping and logging built in. It's the difference between a governed integration and a dangerous one.
MCP server architecture
Define exactly which tools, APIs and data the server exposes, and their schemas.
Custom connectors
Build connectors to your existing systems instead of requiring a rebuild.
Least-privilege access
Scope every tool call so agents reach only what their task requires.
Audit logging
Log tool usage so access patterns can be reviewed and scopes adjusted over time.
Architecture model
A practical delivery architecture before implementation begins.
We define the target operating model, controls, integration points and ownership path before building, so the solution can be supported after launch.
CloudevTech
Enterprise delivery model
01
Discover
02
Architect
03
Implement
04
Validate
05
Operate
Our approach
Structured delivery from discovery to operational handover.
Every engagement is shaped around the service goal, current constraints and the operating model your team needs after launch.
Define tool contracts
Specify exactly which tools, APIs and data the MCP server will expose, and their schemas.
Design access control
Build authentication and least-privilege scoping into the server, not as an afterthought.
Build the mediation layer
Implement the MCP server and connect it to the target systems and AI clients.
Audit and refine
Log tool usage and adjust scopes as real usage patterns emerge.
Business benefits
Outcomes designed for decision makers and delivery teams.
Benefits are framed around measurable improvement, operating confidence and reduced delivery risk.
Mediated tool access
MCP servers sit between agents and production systems as a controlled access layer.
Consistent connector pattern
Custom connectors follow one architecture instead of ad hoc integrations.
Least-privilege by design
Scoped access and audit logging limit what each connected agent can reach.
Technology stack
Implemented with proven platforms and tools.
Technology choices are confirmed during discovery, with a preference for reliable, maintainable platforms your team can support.
MCP
OAuth 2.0
API gateways
GKE
BigQuery
Enterprise AI agents needed access to production tools. Security needed to sleep at night.
Controlled AI-agent tool access with least-privilege scoping, mediated APIs and BigQuery audit logging.
Read the story ->
FAQ
Common questions before engagement.
Short answers to common planning questions for MCP Development.
What's the advantage over direct API access?
MCP puts a governed, auditable layer between the AI and your systems, so access is scoped and logged rather than open.
Can you connect to our internal APIs?
Yes — that's the main use case: mediated, least-privilege access to your existing services.
Enterprise consultation
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