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Agentic Automation (MCP) Solution 

Run AI driven actions on enterprise systems with enterprise level controls. 
 

We provide MCP infrastructure that makes agentic automation safe to deploy, operate and govern.  

What is Agentic Automation (MCP) Solution? 

A governed MCP infrastructure, deployed in your environment, that standardises how AI agents interact with enterprise systems. Agents, whether built in OpenAI Studio, n8n or bespoke code, consume MCP tools exposed through this infrastructure. It enables enterprises to:  

Deploy and manage MCP servers consistently 

Expose internal APIs as MCP tools safely 

Enforce environment separation and lifecycle controls 

Apply governance, logging and auditability 

Operate MCPs reliably in production 

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Common Issues While 
Adopting Agentic AI

The problem is not the capability of AI agents. The problem is the absence of production grade infrastructure.

  • MCP servers are deployed independently by different teams 

  • Internal APIs are exposed without clear controls 

  • There is no single view of which MCPs are active 

  • Tool changes disrupt agents running in production 

  • Development and production environments are not clearly separated 

  • Security and operations teams lack visibility

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MCP servers lack lifecycle and version control 
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Changes move between environments without control 
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Teams cannot observe what is happening in real time 
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Executed actions leave no audit record 
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Ownership is unclear after agents go live 

Why MCP Breaks in Production

MCP adoption fails in production without a dedicated infrastructure layer. 

MCP Infrastructure Architecture

The hidden engineering failures behind enterprise MCP systems.

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Everything required to Run MCP in production

  • Self service MCP server setup through a governed interface 

  • A central registry for all MCP servers across the organisation 

  • Clear separation between development and production environments 

  • Controlled promotion and rollback of MCP servers and tools 

  • MCP tool updates without service interruption 

  • Configuration managed through source control 

  • Secure conversion of internal APIs into MCP tools 

  • Governance controls and audit records for every execution 

  • Centralised logs with end-to-end traceability 

  • Operational dashboards with alerts 

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Production Grade Observability

Everything required to monitor, manage and review MCP activity.

  • End-to-end visibility into every MCP tool execution 

  • Early detection of failures with clear alerts 

  • Usage and performance data for ongoing oversight 

  • Complete audit records for compliance and investigation 

  • Documented operational processes and handover 

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License & Ownership Model 

You own the platform, end to end. The solution is delivered in a way that keeps ownership and control with the client.

  • Provided under a perpetual license 

  • Full source code handed over at delivery 

  • Deployed entirely within the client environment 

  • No reliance on Cloudaeon hosted services 

  • No per-agent or usage based fees 

Delivery and Commercial Model

A clear path from implementation to ongoing operation.  

One Time Implementation

This phase establishes the foundation.

  • This phase establishes the foundation. 

  • Architecture finalisation 

  • Deployment of MCP infrastructure 

  • Environment setup with governance controls 

  • Knowledge transfer to internal teams 

Ongoing Managed Support (Optional)

This phase establishes the foundation.

  • MCP operations delivered under defined SLAs 

  • Monitoring, upgrades, and optimisation 

  • Governance and policy adjustments over time 

  • Support for onboarding new MCP servers and tools 

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Agentic Automation Solution is No

  • Not an agent builder 

  • Not a workflow orchestration tool 

  • Not a low code automation platform 

  • Not a SaaS service 

It is the infrastructure and governance layer that makes agentic automation safe in production. 

The Enterprise MCP Lifecycle Framework

MCP Infrastructure Provisioning Accelerator 

Pre-built Terraform modules, used behind the UI, that prevent one-off deployments and ensure auditability. 
 
Results: 

  • Rapid, repeatable MCP server provisioning 

  • Standardised networking, identity  and security 

MCP Environment & Promotion Framework

Clear environment separation with controlled promotion, designed to protect production systems. 

Results:

  • Safe testing of MCP tools 

  • Zero risk production changes 

API-to-MCP Adapter Framework

API adapter patterns that make MCP adoption scalable across enterprise systems. 
 
Results:  

  • Converting legacy and modern APIs into MCP tools 

  • Consistent governance across tools

MCP Zero Downtime Deployment Pattern 

Live MCP tool updates designed to avoid downtime in production environments. 
 
Results: 

  • Safe tool changes without agent disruption 

MCP Observability & Audit Baseline

Built-in observability that provides full visibility into MCP execution and builds trust with operations and security teams. 
 

Results: 

  • Faster troubleshooting 

  • Compliance readiness 

FAQs

  • The Agentic Automation (MCP) Solution is a governed MCP infrastructure and control plane deployed directly into your environment. It standardises how AI agents safely interact with enterprise systems by providing lifecycle management, governance, observability, and auditability for MCP servers and tools, turning experimental agent usage into production-ready automation. 

  • No. This solution does not build, orchestrate, or manage AI agents. Agents remain external and can be built using OpenAI Studio, n8n, or bespoke frameworks. The solution focuses solely on the infrastructure, governance, and operational control required to safely expose MCP tools that agents consume.

  • MCP implementations fail not because of agent intelligence, but due to lack of infrastructure and governance. Common failure points include ad-hoc MCP deployments, no versioning or lifecycle control, no environment separation, no audit trail, and no operational observability. Without a control plane, MCP usage becomes unmanageable at scale. 

  • Security and compliance are enforced through environment isolation (Dev/UAT/Prod), execution governance, audit logging, GitOps-based configuration management, and full traceability of MCP tool execution. This ensures every action taken by an agent is visible, auditable, and compliant with enterprise change-control and regulatory requirements. 

  • The MCP infrastructure is deployed entirely within the client’s environment. There is no dependency on Cloudaeon-hosted services, no SaaS runtime, and full source code is handed over under a perpetual license, ensuring complete ownership and operational control. 

Ready to Run Agentic AI in Production? 

Let’s understand what’s required to run MCP in production. 

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