How to Use the Donorbox MCP in AutoGen

Deploy a multi-agent team in AutoGen to manage Donorbox campaigns through internal debate and consensus.

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Connect Donorbox MCP to AutoGen

Create your Vinkius account to connect Donorbox 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 Donorbox with AutoGen

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Multi-agent audit of Donorbox

Assign one agent to `quick_campaign_performance_audit` and another to verify the results. They debate discrepancies before presenting a final report. This process ensures your data is accurate before you take action. The agents check each other's work to catch potential issues in your campaign metrics.

Consensus-based donor management

Use a security agent to check `list_registered_donors` for compliance while a marketing agent plans outreach. They negotiate the best strategy for donor communication. You get a balanced approach that respects both privacy and engagement goals. The agents reach an agreement based on the data provided by the API tools.

Automated plan monitoring in AutoGen

One agent tracks `list_recurring_donation_plans` while another evaluates churn risk. They discuss the findings to prioritize which plans need attention. You move faster because your agents do the heavy lifting of data interpretation. They arrive at a conclusion that matches your business priorities.

Setup guide

Set up Donorbox 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 Donorbox 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="Donorbox_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Donorbox 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 Donorbox. 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.

Why Choose Vinkius

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Common questions about Donorbox MCP in AutoGen

You pass the MCP tools to the agent constructor. They use these tools to gather the data needed for their internal debates.

Yes, that is the point of the framework. They challenge each other to ensure the final conclusion is solid.

Your agents can include a logic gate to check rate limits. This prevents them from spamming the API during a long debate.

The agents only execute the tools you allow. You define the scope, and they work within those boundaries to keep your data secure.

They access donor names, emails, and donation totals. This sensitive information is only shared between agents during the deliberation process.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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