How to Use the CPSC (Consumer Product Safety Commission) MCP in AutoGen

Q: How can one AutoGen agent tell another about a CPSC (Consumer Product Safety Commission) recall it found?

The agent that calls searchrecalls simply includes the results in its next message to the group. The other agents in the conversation can then read that message and use the CPSC recall information in their own responses.

Q: Can I create a specialized AutoGen agent just for CPSC (Consumer Product Safety Commission) compliance?

Yes, this is a powerful pattern. You can create an AssistantAgent whose primary job is to use the searchrecalls tool and interpret CPSC data. It can then present its findings to other agents for discussion.

Q: Can I use this MCP server to search for things other than safety recalls?

No. This server provides a single tool, searchrecalls, which is purpose-built to connect your agent to the CPSC's public recall database.

Let your AutoGen agents debate CPSC product recalls to decide on the right compliance and safety actions.

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Setup CPSC (Consumer Product Safety Commission) with AutoGen

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Drive Agent Debates with CPSC Data

One agent in your AutoGen setup can act as the "researcher." It uses the `search_recalls` tool to pull down official CPSC product recall notices. This data then becomes the central topic of conversation. A "risk analyst" agent can argue about the severity of a hazard, while a "communications" agent drafts a customer notification. The recall data fuels the debate.

Simulate a Compliance Team with AutoGen

Build a multi-agent system that mirrors a real-world team. Your "product manager" agent can ask for a check on a new item. The "compliance" agent uses `search_recalls` and reports back. If a recall is found, the agents can then collaborate on a response plan. AutoGen's conversational model means they'll discuss options and reach a consensus, just like people would. This MCP Server gives them the key external data they need.

Automate Product Safety Audits

An "auditor" agent can be programmed to periodically scan a product catalog. For each product, it calls `search_recalls` through this MCP connection. When it finds a match in the CPSC database, it can initiate a conversation with other agents to verify the finding and kick off an internal review process. You're building a system of checks and balances, not just a simple script.

Setup guide

Set up CPSC (Consumer Product Safety Commission) 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 CPSC (Consumer Product Safety Commission) 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="CPSC (Consumer Product Safety Commission)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent CPSC (Consumer Product Safety Commission) 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="CPSC (Consumer Product Safety Commission)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent CPSC (Consumer Product Safety Commission) 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 CPSC. 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 CPSC (Consumer Product Safety Commission) MCP in AutoGen

The agent that calls `search_recalls` simply includes the results in its next message to the group. The other agents in the conversation can then read that message and use the CPSC recall information in their own responses.

Yes, this is a powerful pattern. You can create an `AssistantAgent` whose primary job is to use the `search_recalls` tool and interpret CPSC data. It can then present its findings to other agents for discussion.

That's the point of AutoGen. The agents will continue the conversation, presenting arguments and counter-arguments, until they reach a consensus or a human moderator steps in. The framework is designed for this kind of structured debate around data from the MCP Server.

No. This server provides a single tool, `search_recalls`, which is purpose-built to connect your agent to the CPSC's public recall database.

While the CPSC data is public, the Vinkius platform ensures the connection itself is secure. Each request for recall information from your agent runs in a zero-trust, ephemeral instance. The entire environment is torn down after your query completes, leaving no trace of your agent's activity.

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