Cato MCP Server

The Cato MCP Server is a lightweight, Docker‑based Model Context Protocol implementation that bridges AI assistants—such as Claude Sonnet 4 or Cursor—to the Cato Networks Cloud‑Managed Access (CMA) platform via its GraphQL API. By exposing a set of well‑defined tools, the server enables conversational agents to query real‑time network data, discover assets, and retrieve configuration details without the need for custom code or manual API calls. This removes a significant friction point for developers who want to embed network intelligence directly into AI workflows, allowing them to ask natural‑language questions and receive structured answers from their Cato environment.

At its core, the server provides a collection of tools grouped by category: Entity Lookup, Sites, and Socket Versions. The tool can enumerate users, sites, services, or other entity types, supporting optional filters and pagination so that assistants can drill down into specific subsets. Site‑centric tools such as , , and expose rich metadata—including geographic coordinates, PoP connectivity, operational status, high‑availability state, and interface health—making it straightforward for an AI to map network topology or troubleshoot outages. The tool lists all deployed Sockets and their firmware versions, which is useful for compliance checks or upgrade planning. Each tool returns JSON‑structured data that the AI can parse, summarize, or transform into visualizations.

The server is designed to integrate seamlessly with MCP‑compliant clients. Once the Docker image () is registered in a client’s configuration, the assistant automatically discovers the available tools and can invoke them with natural language prompts. The flag ensures that the latest image is fetched on each launch, keeping the toolset up to date without manual intervention. For developers who prefer tighter control over image updates, disabling this flag is also supported.

Real‑world use cases include automated network monitoring dashboards that pull live data into a conversational interface, on‑call incident response bots that can query site health and connectivity status in seconds, or compliance auditors who need to retrieve firmware inventories across all edge devices. Because the server speaks GraphQL, it can leverage Cato’s powerful filtering and pagination mechanisms, delivering only the data needed for a given query and keeping latency low. This makes it especially valuable in environments where network visibility is critical, such as large enterprises or multi‑cloud deployments.

In summary, the Cato MCP Server turns a complex network API into an intuitive set of AI‑friendly tools. It eliminates the need for bespoke integrations, reduces development time, and empowers developers to build smarter, data‑driven assistants that can answer network questions on demand.