How to Use the NumVerify MCP in AutoGen
AutoGen agents debate phone validity and carrier risks before updating your systems.
Works with every AI agent you already use
…and any MCP-compatible client
Connect NumVerify MCP to AutoGen
Create your Vinkius account to connect NumVerify 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.
Let agents debate phone risk using `validate_phone`
The `validate_phone` tool provides structural validation and carrier metadata for any phone number. In an AutoGen setup, a security agent runs this tool to check incoming signups. It then passes the output to a compliance agent to decide if the user is high-risk. If the number is flagged as invalid, the agents debate whether to block the registration or request an alternative contact method. This automated conversation ensures that only valid, high-quality numbers get written to your database.
Block VoIP fraud using `get_phone_line_type`
The `get_phone_line_type` tool identifies virtual numbers, landlines, and mobile phones. A fraud-detection agent uses this tool to flag VoIP numbers, which are often used for bulk spam signups. The fraud agent presents its findings to a product agent. They negotiate whether to allow the signup with extra verification or block it entirely. This consensus-driven approach keeps your user base clean without requiring manual review.
Route leads via this MCP Server
This MCP Server helps agents determine where a user is located and who provides their phone service. The `get_phone_location` tool extracts geographic data, while `get_phone_carrier` identifies the network provider. Your sales routing agent and support routing agent discuss these details to assign the lead. They look at the geographic region and carrier to determine the best agent to handle the account, resolving any assignment conflicts automatically.
Set up NumVerify 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 NumVerify 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="NumVerify_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent NumVerify 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="NumVerify_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent NumVerify 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 NumVerify. 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 NumVerify MCP in AutoGen
Use it with your favorite AI tools
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