MCP for DevOps, NetOps, and SecOps: Actual-World Use Instances and Future
Insights
Within the earlier publish on MCP for DevOps: Structure and Parts, we mentioned what MCP is and isn’t. We dove into a couple of architectural parts and gently touched on use circumstances. Now, let’s discover a couple of attainable use circumstances for MCP in DevOps/NetOps/SecOps.
I’ve cherry-picked a couple of buyer and associate use circumstances I’ve personally labored with and located applicable for our dialogue. My checklist is not going to be exhaustive, but it surely ought to provide you with a stable view of sensible makes use of for MCP. Let your thoughts ponder the chances in your setting. 😃
Within the YouTube collection on MCP for DevOps, we’ll leverage some use circumstances to construct a working implementation with MCP, instruments, and Cisco merchandise.
Recap – Mannequin Context Protocol (MCP)
In the event you didn’t catch half 1 on this weblog collection on MCP for DevOps: Structure and Parts, test it out. However for now, right here’s a fast level-set on MCP.
As illustrated in Determine 1, the Mannequin Context Protocol (MCP) offers a uniform solution to combine an AI mannequin into instruments and providers.
Determine 1. MCP with LLMs and Instruments
MCP Overview
It’s:
- A light-weight communication protocol designed particularly for AI brokers and functions.
- Constructed to attach these brokers to instruments, APIs, databases, and file methods.
- Structured as a consumer/server structure—easy and predictable.
- Plumbing
It isn’t:
- A messaging protocol for agent-to-agent communication.
- An LLM, database, AI assistant, or agent.
- A general-purpose integration platform.
- A alternative to your current APIs or information bus.
Frequent MCP Use Instances
As talked about above, MCP integrates AI functions, instruments, information sources, APIs, and so forth. Nonetheless, MCP, being a protocol, doesn’t work alone. A consumer and server should use the protocol and full the pairing.
When AI functions and brokers combine the MCP SDK for consumer use and create an MCP server to work on behalf of native or distant instruments, the next typical use circumstances can facilitate a low-toil/high-reward consequence.
-
Automating Routine Duties:
MCP can deal with repetitive chores similar to producing stories, managing GitHub repos, constructing Ansible playbooks, and managing CI/CD pipelines. -
Unified Information and Motion Administration:
Consider MCP as your AI software or agent’s centralized hub for interacting with various methods similar to observability options from Splunk, orchestration methods similar to Cisco NSO, and AI safety platforms similar to Cisco AI Protection. -
Enhanced Context and Resolution-Making:
MCP-powered AI functions and brokers present richer context by accessing information from a number of sources, resulting in quicker, smarter choices. -
Compliance and Safety:
MCP interactions throughout your methods could be safe, compliant, and auditable when used with standardized safety protocols, processes, and instruments.
As illustrated in Determine 2, the MCP Shopper (AI software, assistant, or agent) can use MCP Servers to combine with a number of automation, observability, safety, and collaboration methods by calling these by APIs, information sources, and so forth.
Determine 2. MCP with Instruments, Providers, Platforms
Unified Automation with MCP
DevOps Use Instances
-
CI/CD Automation:
AI functions utilizing MCP can automate total CI/CD pipelines, seamlessly managing builds, exams, deployments, and notifications by Cisco Webex. -
Environment friendly Code Administration:
GitHub MCP integration allows an AI software or agent to handle branches, evaluate pull requests, triage points, and scan for vulnerabilities. -
Infrastructure Automation:
With MCP Server integrations for Terraform and Ansible, your AI agent can shortly and precisely provision infrastructure or modify settings. -
Streamlined Incident Response:
Cisco Webex built-in with MCP helps your AI software or agent actively have interaction in troubleshooting and incident administration, considerably decreasing response instances.
DevOps Situation:
Think about asking your AI software (Chat interface and even your IDE):
“Create a brand new launch department, run exams, deploy to staging, and ship a notification to Cisco Webex.”
As illustrated in Determine 3, your AI software seamlessly orchestrates actions through GitHub, Docker, and Jenkins utilizing MCP and sends updates by Cisco Webex.
Determine 3. MCP-Powered CI/CD Pipeline
Pipeline Automation with MCP
NetOps Use Instances
-
Dynamic Community Administration:
MCP allows AI-driven administration of community configurations utilizing pure language, leveraging Cisco APIs or Infrastructure-as-Code (IaC) instruments. -
Automated Community Monitoring:
With MCP, you should use an AI software or agent to watch community efficiency, detect anomalies, and mechanically remediate points through Cisco options like ThousandEyes, Meraki Dashboard, and plenty of extra. -
Cloud Infrastructure Automation:
MCP permits you to use AI to handle cloud-based networking infrastructure, leveraging Kubernetes APIs and Cisco community controllers for clever automation.
NetOps Situation:
“Add a brand new OSPF IPv6 route for the 2001:db8:cafe::1/64 community at Information Middle A.”
As illustrated in Determine 4, utilizing MCP, your AI software makes use of an MCP Server to work together with Cisco APIs and even NETCONF/RESTCONF to make OSPF routing updates. It instantly updates the NetOps crew through Cisco Webex.
Determine 4. AI-driven Site visitors Administration utilizing MCP
Community Automation with MCP
SecOps Use Instances
-
Proactive Menace Response:
AI brokers utilizing MCP swiftly detect and mitigate threats by adjusting firewall settings with Cisco Safe Firewall and mechanically isolating compromised endpoints utilizing Cisco Safe Endpoint. -
Automated Vulnerability Administration:
MCP integrations allow AI to establish vulnerabilities and generate fast infrastructure or host configuration fixes by Ansible playbooks and Terraform suppliers. -
Actual-time Incident Orchestration:
With MCP, AI orchestrates complete incident responses, isolating threats, deploying patches, and alerting groups through Cisco Webex.
As illustrated in Determine 5, the next state of affairs could be realized utilizing MCP:
SecOps Situation:
Upon receiving a notification that the system recognized malware, your AI assistant makes use of numerous instruments through MCP to instantly:
- Isolates the contaminated gadget utilizing Cisco Safe Endpoint APIs
- Applies fixes by Ansible
- Updates firewall insurance policies
- Informs your safety crew through Cisco Webex
Determine 5. Incident Administration utilizing MCP
Safety Incident Automation with MCP
I’ve not scratched the floor of what’s attainable utilizing AI, MCP, and an limitless array of future MCP servers.
Future Outlook
MCP’s ecosystem continues to develop, promising deeper integrations with Cisco options and broader business adoption. Anticipate extra subtle cross-domain orchestration, streamlined cloud-hosted providers, and AI-driven proactive optimizations. MCP is setting the stage for smarter, quicker, and safer tool-based operations.
Issues to contemplate:
Whereas MCP is nice for AI functions interacting with exterior instruments and information sources, right now, it isn’t constructed for production-grade agent-to-agent composition, deployment, discovery, connectivity, or lifecycle administration of brokers. MCP isn’t but constructed to handle the dynamic discovery of MCP Servers and the instruments they symbolize.
It’s also a Wild Wild West present on MCP Servers. Everyone seems to be creating them. That’s nice because it reveals curiosity in MCP and the way straightforward it’s to leverage the MCP SDK, indicating that MCP offers direct worth. Nonetheless, I warning you to fastidiously consider the MCP servers you leverage in your enterprise use circumstances. Downloading and utilizing an unknown MCP Server that anybody can publish might trigger hurt for those who don’t perceive the instruments, assets, and so forth., the MCP Server is constructed to make use of.
A number of of the various attainable safety implications for MCP use embody:
- Privilege escalation threats
- Observability into what every software name is doing
- Dependency on further code and packages for correct end-to-end encryption and belief
There’s a good weblog publish on MCP safety concerns on the group.cisco.com website: Overview of MCP and Its Safety Structure.
Sooner or later, we’ll see providers and instruments that validate the code/picture of a given MCP Server as we do with app shops, container photos, and so forth. Till there’s a standardized and well-understood approach to make sure you aren’t utilizing a dangerous MCP Server, I’d be further vigilant about researching and actually understanding what the server is doing in your behalf.
What’s subsequent? We are going to proceed this collection on MCP for DevOps by entering into the hands-on aspect of MCP use. Keep tuned for some YouTube movies and extra blogs on particular MCP Purchasers and MCP Servers which are nice for Dev/Internet/SecOps.
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