How to Use the Lob MCP in AutoGen
Build multi-agent AutoGen workflows that debate billing disputes and trigger physical checks or letters via the Lob MCP Server.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Lob MCP to AutoGen
Create your Vinkius account to connect Lob 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.
Approve physical checks through AutoGen agent debates
The `create_check` tool prints and mails physical checks using your configured Lob bank account. In AutoGen, a financial agent can propose a check, while a compliance agent reviews the transaction details before giving approval. This debate ensures that you don't print a Lob check without full consensus. If the AutoGen compliance agent flags the amount or the recipient name, the draft is rejected before the tool is executed.
Verify addresses via consensus using this MCP Server
The `verify_us_address` tool standardizes delivery locations to ensure they are mailable before AutoGen triggers a run. An AutoGen data agent can run this verification, while a separate customer service agent decides how to handle any returned errors. If `autocomplete_us_address` fails to find a match, the AutoGen agents debate whether to prompt the user for input or try a fallback address. That's how you prevent automated Lob mail runs from failing due to bad address data.
Design and dispatch letters using AutoGen agents
The `create_letter` tool generates physical mail using HTML templates and merge variables inside your AutoGen workflow. One AutoGen agent can draft the letter's text, while a design agent reviews the HTML template retrieved via `get_template`. Once both AutoGen agents agree the content looks professional, they trigger the Lob mail run. This workflow ensures every physical letter sent to a customer meets your brand standards.
Set up Lob 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 Lob 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="Lob_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Lob 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="Lob_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Lob 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 Lob. 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 Lob MCP in AutoGen
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
Start using the Lob MCP today
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