How to Use the Chuanglan 253 / 创蓝 MCP in AutoGen
Let AutoGen agents debate and coordinate Chuanglan 253 / 创蓝 SMS campaigns and KYC verification steps automatically.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Chuanglan 253 / 创蓝 MCP to AutoGen
Create your Vinkius account to connect Chuanglan 253 / 创蓝 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.
Debate-Driven KYC Verification
This MCP Server exposes identity verification tools directly to your AutoGen multi-agent workspace. Deploy a team of AutoGen agents to manage your user onboarding. A gatekeeper agent can call `verify_identity` to check a user's ID, while a security agent reviews the results and decides if a manual audit is required. If the identity check is ambiguous, the agents discuss the risk. They can call `verify_phone` to run a three-element check on the user's phone number, converging on a decision before granting access to your platform.
Collaborative SMS Campaign Management
This MCP Server lets your marketing and finance agents collaborate on high-volume messaging directly. The marketing agent drafts the copy and calls `send_variable_sms`, while the finance agent monitors the budget using `get_balance`. If the finance agent flags that your account balance is too low, it pauses the campaign. The agents negotiate whether to scale back the list or request a top-up, preventing unexpected delivery interruptions.
Fault-Tolerant MCP Server Delivery
This integration provides your agents with real-time delivery status tracking to ensure critical alerts go through. A delivery agent calls `send_sms` to send an alert, while a monitoring agent continuously checks the status by calling `query_sms_status` and `pull_sms_reports`. If a delivery fails on a domestic route, the monitoring agent debates the next step with the delivery agent. They can decide to fallback to `send_intl_sms` to ensure the user receives the message.
Set up Chuanglan 253 / 创蓝 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 Chuanglan 253 / 创蓝 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="Chuanglan 253 / 创蓝_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Chuanglan 253 / 创蓝 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="Chuanglan 253 / 创蓝_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Chuanglan 253 / 创蓝 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 Chuanglan 253 / 创蓝. 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 Chuanglan 253 / 创蓝 MCP in AutoGen
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
Start using the Chuanglan 253 / 创蓝 MCP today
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