How to Use the Alchemer MCP in AutoGen

Use AutoGen to let agents debate and decide how to act on Alchemer survey feedback.

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Connect Alchemer MCP to AutoGen

Create your Vinkius account to connect Alchemer 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.

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Setup Alchemer with AutoGen

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Perplexity

Debate Alchemer data with AutoGen agents

Create a team where one agent fetches `list_survey_reports` and another analyzes the trends. They discuss the findings until they agree on a summary. You see the conversation history as they negotiate. It’s effective for complex tasks where you need multiple perspectives on the raw data.

Automate Alchemer responses in AutoGen

Let your agents decide when to call `get_account_usage`. If a limit is reached, the agents can debate how to handle the distribution delay. You build systems that handle their own logic. The agents resolve conflicts based on the constraints you define in their system prompts.

Connect Alchemer via AutoGen adapters

The MCP adapter converts survey tools for your agent team instantly. You pass the server tools into the constructor and the agents start talking to the API. Schema conversion happens behind the scenes. You spend your time defining the agent roles rather than writing boilerplate integration code.

Setup guide

Set up Alchemer 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 Alchemer 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="Alchemer_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

Get your connection token →

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="Alchemer_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Alchemer 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 Alchemer. 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 Alchemer MCP in AutoGen

They use the MCP tool adapter to execute API calls as part of their conversation. You define the agents and they handle the tool invocation.

Absolutely. You can set up a reviewer agent to challenge the findings of an executor agent regarding your survey results.

Your survey records are accessed through a secure, ephemeral connection. The agents only see the data they need to complete their assigned task.

Yes, you can include the server in a group chat. Any agent in the group can request data from the surveys if you grant them access.

They see your survey metadata, campaign lists, and response data. They use this information to inform their debates and reach a consensus.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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