How to Use the Equixly MCP in AutoGen
Let your AutoGen agents debate and decide on API security risks, using live pentest data from Equixly to drive consensus.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Equixly MCP to AutoGen
Create your Vinkius account to connect Equixly 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.
Create an Automated Security Review Board
Go beyond simple automation and build a team of agents. Create a "SecurityAnalyst" agent that uses `trigger_scan` and `get_scan_findings` to find flaws. Then, create a "DevOpsEngineer" agent that cares about deployment velocity. When the SecurityAnalyst flags a medium-severity issue, the DevOpsEngineer can argue that it's in a non-critical service (verified with `get_service`) and shouldn't block the release. They debate using the Equixly tool outputs as evidence until they reach a consensus.
Negotiate Remediation Priorities with AutoGen
A single agent might just dump a list of bugs. A multi-agent system can prioritize them. Your "ProductManager" agent can ask for a scan of a new feature branch using `trigger_scan`. Once the "SecurityAnalyst" agent gets the report via `get_scan_findings`, the two agents can discuss the findings. The PM might argue a UI bug is low priority, while the analyst insists an injection flaw is a showstopper. This conversation produces a prioritized backlog, not a raw data dump.
Let Agents Manage the Attack Surface
Set up a conversation between a "ServiceRegistry" agent and a "SecurityOps" agent. The first agent's job is to monitor your infrastructure. The second agent's job is to ensure everything is scanned using this MCP server. When the registry agent detects a new service, it informs the SecurityOps agent, which then uses `create_service` and `upload_api_spec` to add it to Equixly. If an API is retired, one agent can use `delete_service` and inform the others. It's a self-governing system.
Set up Equixly 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 Equixly 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="Equixly_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Equixly 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="Equixly_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Equixly 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 Equixly. 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 Equixly MCP in AutoGen
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