How do I get a Donorbox API Key?

Log in to your Donorbox account, navigate to **Account > API & Integrations**, and you can generate or retrieve your unique API Key from there. You will also need your account email.

Can the agent manage recurring plans?

This integration currently focuses on listing and auditing recurring plans and their status. Modifying plan details or amounts should be managed via the Donorbox dashboard.

Does the integration show donor contact info?

Yes, you can use the list_registered_donors or search_donors_by_email tools to retrieve donor profile details, including their registered email addresses.

Donorbox MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Donorbox
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Donorbox through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Donorbox "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Donorbox?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Donorbox MCP Server

Integrate Donorbox, the powerful and easy-to-use donation software, directly into your AI workflow. Manage your one-time and recurring donations, track donor profiles and subscription plans, monitor fundraising campaigns and progress, and oversee your donation forms using natural language.

Pydantic AI validates every Donorbox tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Donation Oversight — List and retrieve detailed information and payment status for all your received contributions.
Subscription Intelligence — Monitor active recurring donation plans, frequencies, and donor identifiers across your organization.
Campaign Monitoring — Track fundraising campaigns, goals, total raised amounts, and progress percentages to ensure successful outcomes.
Donor Auditing — Retrieve high-level summaries of donor engagement and identify your most loyal contributors instantly.

The Donorbox MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Donorbox to Pydantic AI via MCP

Follow these steps to integrate the Donorbox MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Donorbox with type-safe schemas

Why Use Pydantic AI with the Donorbox MCP Server

Pydantic AI provides unique advantages when paired with Donorbox through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Donorbox integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Donorbox connection logic from agent behavior for testable, maintainable code

Donorbox + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Donorbox MCP Server delivers measurable value.

Type-safe data pipelines: query Donorbox with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Donorbox tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Donorbox and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Donorbox responses and write comprehensive agent tests

Donorbox MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Donorbox to Pydantic AI via MCP:

get_campaign_details

Get detailed settings and progress for a specific campaign

get_donorbox_account_metadata

Retrieve metadata for the current authenticated user

list_active_subscription_plans

Identify recurring plans that are currently in an "Active" status

list_donorbox_donations

List all donations received in your Donorbox account

list_fundraising_campaigns

List all fundraising campaigns configured in Donorbox

list_latest_contributions

Identify the most recently received donations

list_recurring_donation_plans

List all active recurring donation plans

list_registered_donors

List all donors registered in your Donorbox organization

quick_campaign_performance_audit

Retrieve a high-level summary of all campaign success rates

search_donors_by_email

Search for a donor using their email address

Example Prompts for Donorbox in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Donorbox immediately.

"List all recent donations received in Donorbox."

"Show me the performance for campaign 'Save the Oceans'."

"Find the recurring plan for donor 'sarah.jones@example.org'."

Troubleshooting Donorbox MCP Server with Pydantic AI

Common issues when connecting Donorbox to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Donorbox + Pydantic AI FAQ

Common questions about integrating Donorbox MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Donorbox MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.