How to Use the Cisco Meraki MCP in AutoGen

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Connect Cisco Meraki MCP to AutoGen

Create your Vinkius account to connect Cisco Meraki to AutoGen 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 AutoGen

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Perplexity

Consensus-driven Cisco Meraki management

Assign one agent to audit `list_organization_inventory` while another evaluates security compliance. They discuss findings in a shared conversation to agree on the final state of your hardware. This setup prevents rash decisions. The agents challenge each other's analysis of your network data before you ever see a recommendation.

Multi-agent Cisco Meraki diagnostics

Use the `get_device_details` tool to supply facts to your debating agents during a troubleshooting session. One agent acts as the technician, while the other acts as the supervisor. You get a clear record of the deliberation process. The agents negotiate the best path forward based on actual telemetry from your Cisco Meraki dashboard.

Automated Cisco Meraki response logic

Configure an AutoGen assistant to invoke `list_network_devices` whenever a network issue is reported. The agents then work together to identify the likely culprit and propose a fix. Your workflow remains conversational. The agents handle the tedious task of querying the API and interpreting the results, leaving you to approve the final action.

Setup guide

Set up Cisco Meraki MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Cisco Meraki tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Cisco Meraki_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Cisco Meraki data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Cisco Meraki_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Cisco Meraki data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about Cisco Meraki MCP in AutoGen

They use the MCP adapter to execute tools as part of their conversation. Each tool call is presented as a step in the agents' deliberation.

Yes, by having one agent fetch data and another agent perform the comparison logic. They discuss the differences until they reach a conclusion.

The server acts as a firewall between your API key and the agents. You control which tools the agents are allowed to invoke.

No, the McpToolAdapter maps the tools directly into the agent environment. You just pass the tool list and let the system handle the rest.

The agents only see the specific device lists and network summaries requested. We ensure raw authentication tokens are never shared with the agent team.

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