Can I check the total donation history for a specific donor?

Yes! Use the `get_constituent` tool with the Constituent ID to see their core profile, and use `list_transactions` to audit their individual gifts and pledges recorded in Bloomerang.

How do I list all active fundraising campaigns?

Simply ask the agent to `list_campaigns`. It will retrieve all fundraising campaigns configured in your Bloomerang CRM for your review.

Does the integration allow creating new donation transactions?

Currently, the toolset focuses on querying and auditing (listing constituents, checking transactions). For processing active payments and creating complex financial records, we recommend using the Bloomerang web interface or official forms.

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

Name: Bloomerang
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 Bloomerang 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 Bloomerang "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

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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 Bloomerang MCP Server

Connect your Bloomerang donor management system to any AI agent and orchestrate your non-profit fundraising and donor engagement workflows through natural conversation.

Pydantic AI validates every Bloomerang 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

Constituent Oversight — List and retrieve detailed profiles for donors (individuals and organizations).
Transaction Auditing — Query and inspect donation transactions, pledge payments, and recurring gifts.
Fundraising Strategy — List and monitor campaigns, appeals, and funds to track fundraising progress.
Donor Engagement — Access tasks and notes associated with constituents to maintain strong relationships.
CRM Integration — Retrieve core CRM data including donor IDs and contact history straight from your workspace.

The Bloomerang 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 Bloomerang to Pydantic AI via MCP

Follow these steps to integrate the Bloomerang 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 Bloomerang with type-safe schemas

Why Use Pydantic AI with the Bloomerang MCP Server

Pydantic AI provides unique advantages when paired with Bloomerang 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 Bloomerang integration code

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

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

Bloomerang + Pydantic AI Use Cases

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

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

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

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

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

Bloomerang MCP Tools for Pydantic AI (10)

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

create_constituent

Create a new individual constituent

get_constituent

Get details of a specific constituent

get_transaction

Get specific transaction details

list_appeals

List all fundraising appeals

list_campaigns

List all fundraising campaigns

list_constituents

List all constituents (donors)

list_funds

List all fundraising funds

list_notes

List constituent notes

list_tasks

List constituent tasks

list_transactions

List all transactions

Example Prompts for Bloomerang in Pydantic AI

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

"List all our donors in Bloomerang."

"Show the fundraising campaigns we have running."

"Find the last 5 transactions recorded."

Troubleshooting Bloomerang MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Bloomerang + Pydantic AI FAQ

Common questions about integrating Bloomerang 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 Bloomerang MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.