ZigiWave Introduces ZigiOps MCP Solution for Secure AI-to-System Connectivity

ZigiWave unveils MCP support in ZigiOps for secure AI-to-system integration

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ZigiWave has announced the launch of the ZigiOps MCP solution, a new capability that enables large language models like Claude to securely access enterprise systems in real time, without writing code or storing data.

Watch the video below to see a live demo of how ZigiOps MCP connects AI models to real enterprise systems.

Prefer reading? The sections below break down how the ZigiOps MCP solution works and why it matters for secure AI-driven operations.

The Model Context Protocol (MCP) allows AI assistants to query live operational systems through ZigiOps, acting as a secure, controlled bridge between AI and enterprise tools. With MCP enabled, organizations can safely expose selected systems to AI models while maintaining full control over access, security, and data flow.

Unlike traditional AI integrations that rely on data replication or custom development, the ZigiOps MCP solution works entirely in real time. Data is fetched only when requested, validated by ZigiOps, and returned instantly to the AI model. No information is stored, cached, or copied outside the source systems.

ZigiOps UI showing a system instance with “Accessible by AI” set to true, generating a secure MCP endpoint link.
Enabling MCP access in ZigiOps instantly creates a secure endpoint that allows AI models to query live systems in real time.

The video above demonstrates how ZigiOps connects with Claude AI using MCP. Viewers can see how MCP access is enabled directly from the ZigiOps UI, how ZigiOps appears as a custom connector inside Claude, and how Claude can securely query systems such as Jira to retrieve and summarize live data.

Claude AI settings screen displaying the ZigiOps Demo custom MCP connector added using a secure MCP URL.
ZigiOps appears as a custom MCP connector inside Claude, requiring no authentication setup or coding.

The walkthrough highlights a key shift in how AI can be used in IT operations. Instead of relying on static datasets or complex custom integrations, AI can now interact with real systems through governed, auditable, and no-code connections. ZigiOps handles authentication, API calls, and validation behind the scenes, while the AI focuses on analysis and insights.

Claude AI summarizing Jira KAMI project issues and key insights retrieved in real time through ZigiOps MCP.
Claude queries Jira through ZigiOps MCP and returns a real-time summary of project issues and insights without storing any data.

This release reflects a broader industry trend toward AI-assisted operations, where language models augment IT, DevOps, and service management teams by providing fast answers directly from source systems. By combining MCP with its no-code integration platform, ZigiOps enables this model without introducing new security or compliance risks.

Teams interested in exploring how ZigiOps can connect their own tools to AI models can also book a short demo to see MCP in action with their environments.

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FAQ

1

Which AI tools are supported in ZigiOps MCP?

2

What enterprise systems can AI query through ZigiOps MCP?

3

Does ZigiOps store or cache any data accessed by AI models?

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Is coding required to connect AI models to enterprise systems using ZigiOps MCP?

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