3,400+ MCP servers ready to use
Vinkius

FundraisingBox MCP Server for Pydantic AIGive Pydantic AI instant access to 14 tools to Check Fundraisingbox Status, Get Campaign, Get Dashboard, and more

Built by Vinkius GDPR 14 Tools SDK

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

Ask AI about this App Connector for Pydantic AI

The FundraisingBox app connector for Pydantic AI is a standout in the Customer Relationship Management category — giving your AI agent 14 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 FundraisingBox "
            "(14 tools)."
        ),
    )

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

asyncio.run(main())
FundraisingBox
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 FundraisingBox MCP Server

Connect your FundraisingBox account to any AI agent and manage your nonprofit fundraising operations through natural conversation.

Pydantic AI validates every FundraisingBox tool response against typed schemas, catching data inconsistencies at build time. Connect 14 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 Tracking — List all donations with amounts, donors, campaigns, and payment methods, and filter by campaign
  • Recurring Donations — Monitor all active recurring donation subscriptions with frequency and status
  • Donor Management — Browse all donors with contact info, total donated, and donation count; search by name or email
  • Donor History — Retrieve complete giving history for any donor including amounts, dates, and campaign allocations
  • Campaign Monitoring — List all fundraising campaigns with goals, progress, and donation statistics
  • Donation Forms — View all configured donation form widgets
  • Tax Receipts — Access all generated donation receipts for fiscal reporting
  • Dashboard Analytics — Retrieve aggregate fundraising metrics: total raised, donor count, campaign performance, and trends

The FundraisingBox MCP Server exposes 14 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.

All 14 FundraisingBox tools available for Pydantic AI

When Pydantic AI connects to FundraisingBox through Vinkius, your AI agent gets direct access to every tool listed below — spanning donation-tracking, donor-management, recurring-giving, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

check_fundraisingbox_status

Verify connectivity

get_campaign

Get campaign details

get_dashboard

Get fundraising dashboard

get_donation

Get donation details

get_donor

Get donor profile

get_donor_history

Get donor history

list_campaigns

List campaigns

list_donations

List donations

list_donations_by_project

List donations by campaign

list_donors

List donors

list_forms

List donation forms

list_receipts

List donation receipts

list_recurring_donations

List recurring donations

search_donors

Search donors

Connect FundraisingBox to Pydantic AI via MCP

Follow these steps to wire FundraisingBox into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 14 tools from FundraisingBox with type-safe schemas

Why Use Pydantic AI with the FundraisingBox MCP Server

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

01

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

02

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

03

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

04

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

FundraisingBox + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for FundraisingBox in Pydantic AI

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

01

"Show the fundraising dashboard and which campaigns are closest to reaching their goals."

02

"Search for donor 'Schmidt' and show their complete donation history."

03

"List all recurring donations and identify which ones have been active for more than a year."

Troubleshooting FundraisingBox MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

FundraisingBox + Pydantic AI FAQ

Common questions about integrating FundraisingBox MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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