How to Use the InfoVetted MCP in AutoGen
Let specialized AutoGen agents debate and approve candidate background checks using real-time InfoVetted tools.
Works with every AI agent you already use
…and any MCP-compatible client
Connect InfoVetted MCP to AutoGen
Create your Vinkius account to connect InfoVetted 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.
Collaborative candidate screening
The `create_screening_contact` tool registers a new applicant profile to start the AutoGen multi-agent workflow. An AutoGen recruiting agent initializes this profile before passing the InfoVetted contact to a compliance agent. This dual-agent setup ensures that no InfoVetted background check proceeds without explicit AutoGen consensus. You prevent unauthorized screenings by requiring AutoGen agent agreement first.
Consensus-driven vetting via MCP Server
The `create_new_vetting_check` tool triggers background screenings only after your AutoGen agents agree on the required checks. Compliance agents inspect jurisdictional rules while the recruiter agent pushes for speed. Once they reach consensus, AutoGen calls `list_supported_check_types` to verify the selected InfoVetted check is valid. This collaborative process eliminates manual compliance bottlenecks in high-volume AutoGen hiring workflows.
Multi-agent status monitoring and intervention
The `get_vetting_request_status` tool provides real-time updates that your AutoGen monitoring agent analyzes for flags. If an InfoVetted background check returns an alert, the monitoring agent alerts the AutoGen legal specialist. Your AutoGen compliance agent can execute `cancel_active_vetting` if the candidate fails initial InfoVetted criteria. This automated intervention stops unnecessary screening costs instantly inside your AutoGen group.
Set up InfoVetted 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 InfoVetted 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="InfoVetted_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent InfoVetted 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="InfoVetted_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent InfoVetted 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 InfoVetted. 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 InfoVetted MCP in AutoGen
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