How to Use the Cisco Meraki MCP in OpenAI Agents SDK

Q: How do I connect Cisco Meraki to the OpenAI Agents SDK?

Install the openai-agents package via pip. Create an MCPServerStreamableHttp instance pointing to your Vinkius endpoint URL. Pass that MCP Server object into your Agent constructor's mcpservers list.

Build production-ready network auditing agents with OpenAI Agents SDK that safely query Cisco Meraki devices and clients.

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Connect Cisco Meraki MCP to OpenAI Agents SDK

Create your Vinkius account to connect Cisco Meraki to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Cisco Meraki with OpenAI Agents SDK

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Perplexity

Map Meraki Topologies via MCP Server

This MCP server exposes your Cisco Meraki organization structure directly to OpenAI agents. Your deployed agent starts by running `list_meraki_organizations` to find valid targets before dropping into specific locations using `list_organization_networks`. Handoffs between specialized agents work perfectly here. A discovery agent maps the topology, then passes the network IDs to a security agent that pulls the `list_organization_admins` data to check for unauthorized access. Every API call traces back to your OpenAI dashboard for auditing.

Audit Physical Devices with Guardrails

Production systems demand strict boundaries when touching network hardware. You set safety constraints in the OpenAI Agents SDK, then the agent runs `list_organization_inventory` to pull the full list of APs, switches, and firewalls. When an agent spots an offline switch, it fires `get_device_details` using the specific serial number. Your guardrails ensure the agent only reads this telemetry data without hallucinating configuration changes.

Track Network Clients Autonomously

Pulling real-time client data usually means writing custom polling scripts. Now, your OpenAI agent executes `list_network_clients` to grab the active MAC addresses and IP assignments from any Meraki network. The agent pairs this client list with `get_network_summary` to spot traffic spikes or connectivity drops. You configure the agent to run these checks asynchronously, catching issues before the helpdesk gets a ticket.

Setup guide

Set up Cisco Meraki MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Cisco Meraki tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Cisco Meraki tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Cisco Meraki tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Cisco Meraki Agent",
            instructions="You have access to Cisco Meraki tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Cisco Meraki MCP in OpenAI Agents SDK

Install the `openai-agents` package via pip. Create an `MCPServerStreamableHttp` instance pointing to your Vinkius endpoint URL. Pass that MCP Server object into your Agent constructor's `mcp_servers` list.

Yes. The SDK auto-discovers all eight Meraki tools at startup. Set `cacheToolsList=True` in your configuration to skip the discovery phase on subsequent runs and speed up agent boot times.

Every action gets logged straight to your OpenAI dashboard. If a tool fails to fetch the admin list, you see the exact payload the agent sent to the MCP Server. Debugging production agents takes minutes instead of hours.

The Meraki API returns a standard error, which the agent catches and parses. Because you build with guardrails, the agent knows to stop and ask for human confirmation rather than looping endlessly.

Data routing happens inside a V8 Isolate Sandbox that dies the moment your request finishes. Vinkius holds no logs of your MAC addresses, firewall models, or admin emails. Your endpoint token is the only persistent credential.

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