How to Use the idloom MCP in AutoGen
Build AutoGen agent networks that debate and coordinate event registrations, ticket pricing, and invoices in idloom.
Works with every AI agent you already use
…and any MCP-compatible client
Connect idloom MCP to AutoGen
Create your Vinkius account to connect idloom 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 Event Logistics via AutoGen
Let's face it, event planning involves conflicting priorities. By plugging this MCP Server into AutoGen, you can set up a billing agent and an ops agent to debate registration issues. One agent checks `list_invoices` while the other verifies attendee status with `get_attendee`, negotiating discrepancies automatically. Using this collaborative approach ensures registration errors are caught before emails are sent. The agents then use the tool outputs to reach a consensus on whether an attendee's status should be updated.
Automate Registration Audits and Webhooks
Keeping your registration forms aligned with active ticket tiers is tricky. This MCP toolset helps your agent network use `list_registration_forms` to pull form configurations and compare them against actual ticket pricing retrieved via `list_categories`. If a mismatch is found, a security agent can check `list_webhooks` to see if notification systems are active. This multi-agent verification process prevents broken registration flows from going unnoticed.
Reconcile Transactions and Communications
When a payment fails, you need to know why and who to contact. An AutoGen agent can fetch failed payments using `list_transactions` and pass the details to a communication agent that looks up the attendee's contact info via `list_emails`. Decisions on the best course of action are made based on the event details retrieved from `get_event`. They draft the correction email and verify the target address without you having to manually copy-paste a single field.
Set up idloom 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 idloom 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="idloom_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent idloom 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="idloom_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent idloom 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 idloom. 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 idloom MCP in AutoGen
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