How to Use the Fluxguard MCP in AutoGen
Let your AutoGen agents debate visual changes, verify security alerts, and coordinate site audits automatically.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Fluxguard MCP to AutoGen
Create your Vinkius account to connect Fluxguard 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.
Coordinate multi-agent audits in AutoGen
The `list_alerts` and `get_change` tools drive collaborative multi-agent audits. AutoGen lets you run specialized agents that collaborate. You connect this MCP server to have a security agent call `list_alerts` to find modified pages, while a QA agent runs `get_change` to review the visual differences. They debate whether a change is a malicious defacement or a simple marketing update. Once they reach a consensus, they call `acknowledge_alert` to close the issue or escalate it.
Automate visual validation workflows
The `initiate_crawl` and `list_snapshots` tools automate visual validation inside your conversational loops. When a developer deploys code, your AutoGen agents trigger a crawl using `initiate_crawl`. One agent checks the visual snapshot with `list_snapshots` while another checks the DOM changes. This multi-perspective check ensures you do not miss hidden code modifications. The agents negotiate and output a single, verified status report on the deployment.
Dynamic fleet management via MCP Server
The `add_page` and `create_category` tools manage your monitoring fleet programmatically. Manage your entire monitoring footprint through agent conversations. An agent reads a system configuration file and calls `add_page` to expand coverage to new endpoints. They organize these targets on the fly by calling `create_category`. You get an autonomous monitoring setup that adapts to your infrastructure changes without manual code updates.
Set up Fluxguard 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Fluxguard tools and returns structured results.
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="Fluxguard_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Fluxguard data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Fluxguard_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Fluxguard data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Fluxguard. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Fluxguard MCP in AutoGen
Use it with your favorite AI tools
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