Runtime on GKE
The MCP server platform runs on Google Kubernetes Engine for scalability, isolation and repeatable deployment across environments.
AI Platform | Google Cloud
Governed MCP platform connecting enterprise AI agents to production tools.
A governed MCP platform on GKE gave enterprise AI agents controlled, auditable access to production tools.
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Project brief
Controlled AI-agent tool access with least-privilege scoping, mediated APIs and BigQuery audit logging.
A governed MCP platform on GKE gave enterprise AI agents controlled, auditable access to production tools.
01 | Challenge
The operating problem.
The organization wanted AI agents and copilots to take real actions in production systems, such as querying data, triggering workflows and calling internal APIs.
The blocker was governance: direct agent access created serious risk around auditability, authentication and blast-radius control.
Leadership needed agent capability without giving autonomous systems unrestricted access to production.
02 | Delivery approach
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How the solution was delivered.
Identity and access with OAuth 2.0
Every agent and tool call is authenticated and scoped, so agents only reach the tools and data they are authorized to use.
Edge protection with Cloud Armor
WAF and rate-limiting policies protect the platform public surface from abuse and automated attacks.
Managed API access
Production tools are exposed through a governed API layer so connectivity is controlled, mediated and versioned.
Auditability with BigQuery
Every tool invocation is logged to BigQuery, creating a queryable audit trail of which agent did what, when and with what result.
Repeatable delivery with Helm
The platform is packaged as Helm charts so environments remain consistent and reproducible.
Architecture
How the delivery model connected into production.
The architecture view summarizes the workstream sequence, control points and technical path used to move from challenge to operating outcome.
CloudevTech
Enterprise delivery model
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Runtime on GKE
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Identity and access with OAuth 2.0
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Edge protection with Cloud Armor
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Managed API access
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Auditability with BigQuery
03 | Outcome
Production impact with client confidentiality protected.
Published outcomes remain qualitative unless client-approved metrics are available for public use.
Tech stack
Platforms and controls used in the engagement.
Google Kubernetes Engine (GKE)
OAuth 2.0
Google Cloud Armor
API management
Helm
BigQuery audit logging
Model Context Protocol (MCP)
AI & Platform Engineering
This case study connects directly to CloudevTech AI & Platform Engineering delivery.
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