How to Use the Bloomerang MCP in AutoGen

Q: Can AutoGen agents modify Bloomerang records?

They can call the createconstituent tool once the agents agree on the data. The conversation history captures the full rationale for every record creation.

Let your AutoGen agents debate fundraising strategies using live Bloomerang data.

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Connect Bloomerang MCP to AutoGen

Create your Vinkius account to connect Bloomerang 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 Bloomerang with AutoGen

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Debate donor goals with AutoGen

Your agents can now discuss fundraising targets by pulling live numbers. One agent queries `list_campaigns` while another analyzes the ROI, leading to a consensus on where to focus. Disagreements happen in real-time. If the performance agent flags a low-performing fund, the strategy agent must justify keeping it open based on the transaction data.

Resolve Bloomerang tasks via AutoGen

Multiple agents collaborate to complete constituent management tasks. A researcher agent calls `get_constituent`, and the writer agent uses that info to build a donor profile. Consensus-driven decisions ensure accuracy. Before an agent updates a record, it must satisfy the security agent's check on the incoming data format.

Automate Bloomerang workflows in AutoGen

The McpToolAdapter handles the heavy lifting of schema conversion. Your agents interact with the tools natively without worrying about the underlying API structure. Conversation logs show the full reasoning path. You see how the agents shared the results of `list_notes` to arrive at their final recommendation.

Setup guide

Set up Bloomerang 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 Bloomerang 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="Bloomerang_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Agents pass tool outputs back and forth within the conversation loop. One agent retrieves data via `list_transactions`, and the others debate the implications of those figures.

They can call the `create_constituent` tool once the agents agree on the data. The conversation history captures the full rationale for every record creation.

You provide an endpoint token that grants the agents access to your account. This token allows the tools to execute calls against your specific CRM instance.

The adapter automatically converts the tool definitions into a format AutoGen understands. You get a clean list of tools ready for your AssistantAgent.

Your data stays private within your ephemeral sandbox environment. We use zero-trust principles for every tool call, ensuring that only your authorized agents can access or modify constituent information.

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