How to Use the BulkSMS MCP in AutoGen

Q: Can BulkSMS tools be used for multi-agent workflows?

Yes, agents can pass the results of getmessage to one another. One agent can fetch the data, while another interprets the message details and suggests a response.

Q: How do I configure BulkSMS in AutoGen?

Use the mcpservertools function to fetch the schema from the server. Once converted, you assign these tools to your agents to enable direct interaction with your account.

Let your AutoGen agents debate and execute messaging tasks with this BulkSMS integration.

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Setup BulkSMS with AutoGen

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Debate BulkSMS sends in AutoGen

Assign the `send_sms` tool to a specialized agent that monitors your traffic. If a second agent flags a potential issue, they can pause the execution until the parameters are corrected. This multi-agent setup prevents errors before they happen. Your agents reach a consensus before any message actually leaves your account.

Manage messaging with agents

One agent handles `list_messages` to track delivery, while another analyzes the data to suggest improvements. They discuss the findings and iterate on your strategy. This collaborative approach keeps your messaging operations efficient. You don't have to manage the workflow manually; the agents negotiate the best path forward.

Automate credit oversight

Have a dedicated monitoring agent call `get_profile` on a schedule. If it detects a low balance, it alerts the group to stop any pending bulk sends. This creates a safety net for your account. The agents act as a team, ensuring your messaging credits are managed properly without your intervention.

Setup guide

Set up BulkSMS 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 BulkSMS 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="BulkSMS_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent BulkSMS 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="BulkSMS_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by BulkSMS. 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 BulkSMS MCP in AutoGen

You provide the tool list to the AssistantAgent constructor. This allows all agents in your conversation to propose and execute tool calls as part of their collaborative debate.

Yes, agents can pass the results of `get_message` to one another. One agent can fetch the data, while another interprets the message details and suggests a response.

Use the mcp_server_tools function to fetch the schema from the server. Once converted, you assign these tools to your agents to enable direct interaction with your account.

The agents generate requests that the MCP adapter translates into tool calls. This allows them to read your messaging data and perform actions based on their internal logic.

The data returned by the tools is treated as text in the agent conversation window. Your account information and SMS records are never stored in the agent's long-term memory unless you explicitly configure a database to do so.

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