It’s getting actual out right here.
Ever since I shared how autonomous AI Brokers can monitor and heal the community on their very own—sure, that one—I’ve gotten the identical follow-up query in several types:
“Okay, Kareem, this all sounds nice… however how do I truly construct one in every of these Mannequin Context Protocol (MCP) servers for my product?”
Excellent news! In case your product—like virtually each product on the market—has APIs, then chances are high that you have already got what you want.
Enter: OpenAPI spec
OpenAPI is a pleasant contract to your APIs. You would possibly’ve used it for Swagger docs, SDKs, Postman collections, or that one dusty codegen mission from 2021. However right here’s the twist: What should you handed that very same OpenAPI spec to your AI agent?
That’s it. That’s the important thing.
One OpenAPI spec → one MCP Server → one AI-powered, access-controlled gateway to your product.
And no, this isn’t a “12 steps and a DevRel miracle” scenario. It’s only a few strains of Python and a FastMCP wrapper round your OpenAPI file. The magic? Your APIs get reworked into secure, role-based AI instruments—with out writing a single customized software definition.
Take into account the next instance:
You’re wrapping your present OpenAPI spec with FastMCP, wiring in your authenticated consumer, and passing in your route-based ACLs. That’s how easy it’s to go from “API docs” to “AI-ready, access-controlled MCP server.”
Construct quick, govern sensible
On this new AI-powered world, velocity is the simple half. Governance—that’s the tougher carry.
We don’t wish to give the agent the keys to the dominion. We wish to present it with a badge with simply the correct entry.
That’s the place RouteMap is available in—our ACLs for AI. With a easy listing of patterns (regex for individuals who love ache and struggling) and HTTP verbs, you may declare what endpoints are accessible for various personas (NOC, Sysadmin, full entry, and so forth).
Sure, it’s actually that simple. You’re constructing endpoint ACLs as code. You don’t must create an entire new auth system or practice a mannequin to “study” permissions. You simply declare what roles get entry to what endpoints—and the MCP Server enforces it.
From chaos to order
Let’s stroll by way of a real-world use case.
Say you’re a NOC workforce managing a multi-site Meraki deployment. You’re accountable for protecting community units patched and safe—however you may’t simply schedule firmware upgrades at any time. Some websites are 24/7. Some spike at midday. Some run evening shifts. The perfect improve window is a shifting goal.
That’s the place the agent steps in.
You wish to give the agent simply sufficient entry to assist:
- Pull the present firmware standing
- Monitor community utilization patterns
- Schedule upgrades when it is sensible
In the meantime, your Sysadmin workforce wants the agent to generate compliance stories. They should know which units are operating outdated firmware—however they’re not scheduling upgrades or touching dwell site visitors.
Two personas. Two very totally different scopes. One MCP server.
Right here’s the fantastic thing about all of it. We didn’t write any customized instruments. We didn’t construct workflows or hardcode enterprise logic. We simply fed the MCP server the complete Meraki OpenAPI spec—and let RouteMap deal with the remainder:
The NOC agent can schedule upgrades, as a result of it wants that management. The Sysadmin agent? It will get a read-only view, tailor-made for visibility and compliance.
And once more—we didn’t inform the agent how to do something. The magic is within the MCP server. The instruments change into out there primarily based on the function, and the AI figures out the remainder.
That’s the sort of ruled autonomy that turns AI from a danger right into a functionality.
View it in motion
As standard, you’ll discover all the things I’m exhibiting right here—the MCP server code, config, and immediate—in my GitHub Repo.
Now let’s hearth this factor up. (And, sure, Community Pharaoh is a factor now.)
With the MCP server operating and our route maps outlined, I launch Claude Desktop (my MCP consumer of selection) and kind the next immediate:
Your identify is Community Pharaoh. You’re appearing with full administrative visibility and knowledge entry privileges. You’re a senior community administrator overseeing a number of Cisco Meraki organizations throughout the enterprise. Your function is to make sure that all community units are operating the most recent compliant firmware. You’re licensed to advocate firmware upgrades, however you have to watch for specific human approval earlier than initiating any updates.
Goal Organizations: Cisco U.
Activity Directions – For every group:
-
- Checklist all networks
- For every community, listing all related units (together with mannequin, serial, and present firmware model)
- Retrieve the out there firmware improve suggestions for the group
- Determine any system that isn’t operating the really helpful model
- Suggest firmware upgrades as acceptable
- Don’t carry out any improve until the human explicitly confirms with an announcement like: “Sure, please improve [device/network].”
A couple of issues are value calling out:
The human-in-the-loop is in-built. The agent is aware of it can’t act by itself—it should watch for approval. That’s governance baked into the immediate.
We didn’t inform the agent tips on how to verify compliance or recommend upgrades. It makes use of the instruments out there by way of the MCP Server and acts throughout the boundaries outlined by its function.
The agent is doing clever work inside secure boundaries—utilizing solely what it’s been given entry to. No guesswork. No scraping. No uncontrolled API calls. Simply clear, policy-driven interplay by way of a structured, safe interface.
Right here’s what the MCP server config seems like behind the scenes:
Take note of the significance of the MCP_ROLE. This one setting variable controls which routes the agent has entry to. Set it to “NOC” and the agent can advocate firmware upgrades. Set it to “sysadmin” and the identical agent, with the identical immediate, will solely have the ability to generate compliance stories—no upgrades, no PUTs.
That’s the benefit of separating the intelligence (LLM) from the management airplane (MCP). You keep in control of what the agent can do.
And right here’s what the MCP server makes occur:
- Community Pharaoh traverses our Cisco U. group, pulling an inventory of managed units and spitting out a report.
- As Community Pharaoh is ready for a human within the loop to execute the improve, it additionally auto-corrects the model primarily based on internet search and schedules it for us primarily based on utilization.
- Et, voila!
The talents behind the scenes
Let’s zoom in for a second. What did it take to construct this?
Listed here are the abilities a community engineer must put this collectively:
- Understanding of API fundamentals: OpenAPI specs, endpoints, HTTP strategies
- Python scripting: Spinning up a primary server and configuring the MCP wrapper
- Entry management considering: Defining roles, entry boundaries, and implementing least privilege
- Agent design mindset: Prompting with context, goal, and clear human oversight
- Curiosity and experimentation: Making an attempt issues out and tweaking as you go
And perhaps most significantly:
- A shift in considering—from constructing automation for the community, to constructing automation that understands the community.
Let’s maintain pushing this frontier. As a result of the extra we construct clever boundaries, the extra we unlock secure autonomy.
And that’s how we go from the Wild West… to a well-governed AI-powered enterprise.
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