How to Use the CloudCard ID Photos MCP in AutoGen

Q: How do I add CloudCard ID Photos tools to AutoGen agents?

Use mcpservertools with your server URL to fetch the tool definitions. Pass this list to your AssistantAgent constructor so it can run tools like approveidphoto during conversations.

Q: Can AutoGen agents collaborate to deny a photo on CloudCard ID Photos?

Yes, one agent can inspect the submission via listsubmittedphotos and suggest a rejection. A second agent verifies the policy and executes denyidphoto with the agreed reason.

Q: How do AutoGen agents verify system health with CloudCard ID Photos?

Your coordinator agent can run checkapihealth on the MCP server at the start of a session. If the API is offline, the agent halts the conversation and notifies the user.

Run multi-agent debates to approve or deny CloudCard ID Photos inside AutoGen.

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Create your Vinkius account to connect CloudCard ID Photos 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 CloudCard ID Photos with AutoGen

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Multi-Agent Photo Verification

The `list_submitted_photos` tool feeds pending uploads into your AutoGen agent conversation. One agent reviews the photo metadata while another validates cardholder details. They debate the quality using rules from `list_photo_requirements`. Once they reach a consensus, the execution agent calls `approve_id_photo` or `deny_id_photo` based on their decision.

Onboarding via this AutoGen MCP Server

By invoking `register_new_cardholder`, your agent swarm adds new profiles to the system. Before registering, a validator agent checks the email format while a coordinator agent checks the office locations. They coordinate using `list_card_offices` to assign the cardholder to a valid distribution center. This prevents invalid profiles from being created without team consensus.

System Auditing and Webhook Management

Calling `list_configured_webhooks` lets your security agent inspect active event listeners. If a webhook looks misconfigured, the agent alerts the admin agent in the chat. Your conversation logs this audit alongside metadata from `get_organization_settings`. This keeps your integration secure and verified by multiple autonomous perspectives.

Setup guide

Set up CloudCard ID Photos 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 CloudCard ID Photos 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="CloudCard ID Photos_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent CloudCard ID Photos data")
print(result.messages[-1].content)

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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="CloudCard ID Photos_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent CloudCard ID Photos data")
    print(result.messages[-1].content)

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Common questions about CloudCard ID Photos MCP in AutoGen

Use `mcp_server_tools` with your server URL to fetch the tool definitions. Pass this list to your `AssistantAgent` constructor so it can run tools like `approve_id_photo` during conversations.

Yes, one agent can inspect the submission via `list_submitted_photos` and suggest a rejection. A second agent verifies the policy and executes `deny_id_photo` with the agreed reason.

Your coordinator agent can run `check_api_health` on the MCP server at the start of a session. If the API is offline, the agent halts the conversation and notifies the user.

Yes, you can set up a workflow where one agent parses a CSV of names and emails. It then passes each record to another agent that executes `register_new_cardholder`.

Completely. Cardholder PII, including emails and names, is processed entirely in memory within a zero-trust V8 sandbox hosted on the MCP platform. No data is stored or logged outside your local AutoGen environment.

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