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 varieties:
“Okay, Kareem, this all sounds nice… however how do I really 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 likelihood is 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 venture from 2021. However right here’s the twist: What in the event 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 traces of Python and a FastMCP wrapper round your OpenAPI file. The magic? Your APIs get remodeled into protected, role-based AI instruments—with out writing a single customized software definition.
Contemplate the next instance:
You’re wrapping your current 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 straightforward half. Governance—that’s the more durable raise.
We don’t need to give the agent the keys to the dominion. We need to present it with a badge with simply the right entry.
That’s the place RouteMap is available in—our ACLs for AI. With a easy listing of patterns (regex for many 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 straightforward. You’re constructing endpoint ACLs as code. You don’t must create an entire new auth system or prepare a mannequin to “be taught” permissions. You simply declare what roles get entry to what endpoints—and the MCP Server enforces it.
From chaos to order
Let’s stroll via a real-world use case.
Say you’re a NOC workforce managing a multi-site Meraki deployment. You’re accountable for conserving 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 need 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 studies. They should know which units are operating outdated firmware—however they’re not scheduling upgrades or touching stay site visitors.
Two personas. Two very completely different scopes. One MCP server.
Right here’s the great 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 total 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 obtainable based mostly on the position, and the AI figures out the remainder.
That’s the type of ruled autonomy that turns AI from a threat right into a functionality.
View it in motion
As ordinary, 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 fireplace 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 sort the next immediate:
Your identify is Community Pharaoh. You might be appearing with full administrative visibility and information entry privileges. You’re a senior community administrator overseeing a number of Cisco Meraki organizations throughout the enterprise. Your position is to make sure that all community units are operating the newest compliant firmware. You might be approved to advocate firmware upgrades, however you could watch for express human approval earlier than initiating any updates.
Goal Organizations: Cisco U.
Process Directions – For every group:
-
- Listing all networks
- For every community, listing all related units (together with mannequin, serial, and present firmware model)
- Retrieve the obtainable firmware improve suggestions for the group
- Determine any machine that’s not operating the advisable model
- Advocate firmware upgrades as applicable
- Don’t carry out any improve until the human explicitly confirms with an announcement like: “Sure, please improve [device/network].”
Just a few issues are value calling out:
The human-in-the-loop is inbuilt. 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 easy methods to verify compliance or counsel upgrades. It makes use of the instruments obtainable via the MCP Server and acts throughout the boundaries outlined by its position.
The agent is doing clever work inside protected boundaries—utilizing solely what it’s been given entry to. No guesswork. No scraping. No uncontrolled API calls. Simply clear, policy-driven interplay via a structured, safe interface.
Right here’s what the MCP server config appears to be like like behind the scenes:
Take note of the significance of the MCP_ROLE. This one surroundings 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 be capable of generate compliance studies—no upgrades, no PUTs.
That’s the benefit of separating the intelligence (LLM) from the management airplane (MCP). You keep answerable for what the agent can do.
And right here’s what the MCP server makes occur:
- Community Pharaoh traverses our Cisco U. group, pulling a listing 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 based mostly on internet search and schedules it for us based mostly on utilization.
- Et, voila!
The abilities behind the scenes
Let’s zoom in for a second. What did it take to construct this?
Listed below are the talents a community engineer must put this collectively:
- Understanding of API fundamentals: OpenAPI specs, endpoints, HTTP strategies
- Python scripting: Spinning up a fundamental server and configuring the MCP wrapper
- Entry management pondering: 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 pondering—from constructing automation for the community, to constructing automation that understands the community.
Let’s hold pushing this frontier. As a result of the extra we construct clever boundaries, the extra we unlock protected autonomy.
And that’s how we go from the Wild West… to a well-governed AI-powered enterprise.
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