How to Use the FundraisingBox MCP in OpenAI Agents SDK
Build production-grade OpenAI Agents with this MCP Server to safely pull FundraisingBox donation metrics and verify donor histories.
Works with every AI agent you already use
…and any MCP-compatible client
Connect FundraisingBox MCP to OpenAI Agents SDK
Create your Vinkius account to connect FundraisingBox to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Secure FundraisingBox MCP Server tools for OpenAI Agents
Your OpenAI agent can now verify live FundraisingBox donor status and check historical records using `get_donor_history` and `get_donor` without manual exports. By running these tools within the agent's execution loop, your system retrieves live CRM records on demand. The OpenAI Agents SDK manages these calls safely, ensuring your agent only accesses the exact files needed to draft donor communications. This MCP Server connects directly to your secure endpoints, allowing your custom OpenAI agents to pull active campaign lists using `list_campaigns`. You don't have to write custom API wrappers for FundraisingBox or handle complex token exchanges inside your OpenAI script. The agent discovers the tools autonomously, so you can focus on building multi-agent handoffs for your fundraising operations.
Safe FundraisingBox reporting with native OpenAI guardrails
Automating FundraisingBox financial reporting using `list_receipts` or `list_donations` requires strict execution guardrails to prevent bad data from leaking into your accounting. The OpenAI Agents SDK lets you validate arguments before executing these calls. If an OpenAI agent attempts to retrieve records with invalid date ranges, your validation layer catches the error before the API call runs. You can trace every step of this process directly inside your OpenAI developer dashboard. When an agent calls `get_dashboard` to compile a morning fundraising report, you see the exact input parameters and JSON outputs. This transparency makes it easy to debug complex workflows like auditing FundraisingBox donor receipts or tracking campaign progress.
Automated FundraisingBox subscription tracking via OpenAI
Managing FundraisingBox subscription gifts is easier when you split the work using `list_recurring_donations` between specialized OpenAI agents. You can deploy one agent to monitor incoming subscriptions and another to update donor profiles using `get_donor`. The OpenAI Agents SDK handles the transition between these agents, passing context without losing track of the donor's ID. If a recurring payment fails, the system triggers a lookup using `search_donors` to locate the correct contact details. The OpenAI agent then hands off the task to a messaging specialist to draft a friendly reminder. This keeps your FundraisingBox donor relations running smoothly without manual intervention.
Set up FundraisingBox MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all FundraisingBox tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives FundraisingBox tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate FundraisingBox tools and returns structured results. Copy the full example on the right to get started.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse
async def main():
async with MCPServerSse(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as server:
agent = Agent(
name="FundraisingBox Agent",
instructions="You have access to FundraisingBox tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by FundraisingBox. 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 FundraisingBox MCP in OpenAI Agents SDK
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