Mannequin Context Protocol (MCP) servers present a brand new method to unify automation and observability throughout hybrid Cisco environments. They allow an AI shopper to mechanically uncover and use instruments throughout a number of Catalyst Heart clusters and Meraki organizations.
If you happen to’re interested by how this works, now’s the time to see it in motion.
On this new demo, Cisco Principal Technical Advertising and marketing Engineer Gabi Zapodeanu reveals how a single AI shopper routes natural-language queries to the proper software, retrieves responses from a number of domains, and helps you troubleshoot or report in your community extra effectively.
See MCP in Motion: Catalyst Heart and Meraki Integration
Within the video under, Gabi demonstrates how MCP servers allow an AI shopper to work together with instruments throughout a number of platforms. You’ll be taught:
- How the shopper connects to a number of MCP servers and discovers accessible instruments.
- How these instruments are chosen and executed in actual time primarily based on person intent.
- How a single question can span clusters and organizations utilizing patterns like cluster = all.
The video consists of sensible walkthroughs of multi-cluster stock lookups, challenge correlation throughout, and a BGP troubleshooting workflow constructed from primary instruments.
Understanding MCP Structure and Workflow
MCP makes use of a client-server protocol that permits an AI assistant to hook up with a number of MCP servers and dynamically uncover accessible software definitions. Here’s what the total workflow seems to be like:
- An AI shopper, powered by a big language mannequin, connects to a number of MCP servers.
- Every server supplies an inventory of instruments—both prebuilt runbooks or auto-generated APIs.
- A person asks a query; the AI shopper selects the suitable software, fills within the parameters, and sends the request.
- The instruments execute, return information, and the AI responds to the person.
This allows asking a single query—resembling “The place is that this shopper related?”—and receiving solutions from a number of clusters and organizations.
Crucial Instruments vs. Declarative Instruments in MCP Servers
The demo explains two sorts of instruments supported by MCP servers:
- Crucial instruments are predefined sequences written in Ansible, Terraform, or Python. They’re finest suited to write duties the place guardrails and strict execution order are necessary.
- Declarative instruments are auto-generated from YAML recordsdata and are perfect for read-heavy duties resembling stock, occasion lookup, or compliance checks. In addition they help pagination with offset and restrict parameters.
Gabi shares examples of each sorts, demonstrating their use in actual eventualities like firmware checks and cross-domain shopper discovery.
Troubleshooting and Compliance Utilizing Generative AI Flows
Past single-tool calls, MCP helps multi-step workflows. These generative AI flows allow you to:
- Correlate occasions
- Establish root causes of points resembling BGP flaps
- Run compliance checks or acquire telemetry throughout websites
- Apply guardrails for modifications, guaranteeing solely trusted runbooks are used for configuration actions
The MCP shopper learns from software utilization patterns and might recommend new instruments primarily based on frequent API calls.
Find out how to Get Began and What’s Subsequent
This demo supplies a transparent, sensible introduction to MCP for anybody working in NetOps or DevOps. You’ll achieve a greater understanding of:
- Why MCP issues right this moment
- Find out how to join MCP to your Cisco platforms
- The sorts of instruments and workflows it helps
- Find out how to construction your personal instruments utilizing YAML or SDKs
Watch the total replay:
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