How to Use the Classy.org MCP in AutoGen
Let AutoGen agents debate and coordinate campaign strategies using real-time Classy.org fundraising data.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Classy.org MCP to AutoGen
Create your Vinkius account to connect Classy.org 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.
Multi-agent debate on Classy.org campaign performance
The Classy.org MCP Server gives AutoGen agents direct access to `get_campaign_details` and `list_fundraising_campaigns` during group debates. A marketing agent can analyze the data and propose a new push, while a finance agent challenges the assumptions based on actual transaction trends. The agents use `list_donation_transactions` to back up their arguments with hard numbers. This collaborative analysis ensures that your fundraising strategies are vetted by multiple perspectives before any decisions are made.
Coordinate donor outreach using the Classy.org MCP Server
Exposing `list_classy_members` and `get_activity_feed` to your AutoGen group chat lets your agents coordinate donor outreach dynamically. One agent identifies high-value supporters, while another drafts personalized messages tailored to their recent activities. Because the tools are shared across the AutoGen environment, all agents stay aligned. They use real-time Classy.org data to ensure no donor receives duplicate messages or outdated information.
Optimize peer-to-peer team support dynamically
This Classy.org integration exposes `list_fundraising_teams` and `list_individual_fundraising_pages` to AutoGen for automated team tracking. Your coordinator agent can monitor which teams are falling behind and assign a support agent to draft custom resources for them. The entire process runs autonomously within your agent group. By analyzing real-time standings on Classy.org, your AutoGen agents can deploy targeted encouragement to the teams that need it most.
Set up Classy.org 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Classy.org tools and returns structured results.
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="Classy.org_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Classy.org data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Classy.org_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Classy.org data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Classy.org. 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 Classy.org MCP in AutoGen
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