SIGN UPLOG IN
X (Twitter)LinkedInGitHubDiscordYouTube

How to integrate Blackbaud MCP with Pydantic AI

Connect Pydantic AI to Blackbaud MCP. Create a new donor record for a fundraiser, list recent donations for a specific campaign, and more using natural language, with authentication handled for you.

Get started for freeGet a demo
Blackbaud logoBlackbaud
Oauth2

Blackbaud provides cloud-based software for nonprofits, schools, and healthcare institutions. It streamlines fundraising, donor management, and mission-driven operations.

5 Tools

Introduction

This guide walks you through connecting Blackbaud to Pydantic AI using the Composio tool router. By the end, you'll have a working Blackbaud agent that can add gifts to batches, look up gifts by ID, fetch membership details, and check payment transactions through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Blackbaud account through Composio's Blackbaud MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Blackbaud with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIAutoGen

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Blackbaud
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Blackbaud workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

What is the Blackbaud MCP server, and what's possible with it?

The Blackbaud MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc. directly to your Blackbaud account. It provides structured and secure access to your Blackbaud environment, so your agent can perform actions like managing fundraising campaigns, tracking donor engagement, handling financial records, and supporting nonprofit operations on your behalf.

  • Fundraising campaign management: Enable your agent to create, update, or summarize key fundraising initiatives, track progress, and optimize campaign outcomes.
  • Donor and constituent engagement: Automate the process of tracking donor information, recording interactions, and segmenting engagement strategies for better relationship management.
  • Financial record keeping: Allow your agent to access, update, or reconcile financial transactions, ensuring your organization’s accounts remain accurate and up-to-date.
  • Event planning and management: Let your agent coordinate event logistics, handle registrations, and track attendance to streamline in-person or virtual fundraising events.
  • Grant and gift processing: Support your agent in processing incoming gifts or grants, managing acknowledgments, and keeping detailed records for compliance and reporting.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Blackbaud
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Blackbaud
  • MCPServerStreamableHTTP connects to the Blackbaud MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Blackbaud
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["blackbaud"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Blackbaud tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
blackbaud_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[blackbaud_mcp],
    instructions=(
        "You are a Blackbaud assistant. Use Blackbaud tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Blackbaud endpoint
  • The agent uses GPT-5 to interpret user commands and perform Blackbaud operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Blackbaud.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Blackbaud API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Blackbaud and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Blackbaud
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["blackbaud"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    blackbaud_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[blackbaud_mcp],
        instructions=(
            "You are a Blackbaud assistant. Use Blackbaud tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Blackbaud.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Blackbaud through Composio's Tool Router. With this setup, your agent can perform real Blackbaud actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Blackbaud for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every Blackbaud action and event your agent gets out of the box.

Add Gifts To Batch

Add one or more gifts (donations) to an existing gift batch in Blackbaud Raiser's Edge NXT.

Get Gift By ID

Retrieves comprehensive gift details from Blackbaud Raiser's Edge NXT by gift ID.

Get Membership Details

Retrieves comprehensive membership details from Blackbaud Raiser's Edge NXT by member junction ID.

Get Payment Transaction

Retrieves payment transaction details from Blackbaud SKY Payments API.

OneRoster OAuth2 Base API

Tool to interact with Blackbaud OneRoster OAuth2 base endpoints.

FRAMEWORKS

How to build Blackbaud MCP Agent with another framework

Claude Code logo

Claude Code

Use Blackbaud MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Blackbaud MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Blackbaud MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Blackbaud MCP with Claude Agent SDK

Codex logo

Codex

Use Blackbaud MCP with Codex

OpenClaw logo

OpenClaw

Use Blackbaud MCP with OpenClaw

Hermes logo

Hermes

Use Blackbaud MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Blackbaud MCP with Atomic Agent

Google ADK logo

Google ADK

Use Blackbaud MCP with Google ADK

LangChain logo

LangChain

Use Blackbaud MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Blackbaud MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Blackbaud MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Blackbaud MCP with LlamaIndex

CrewAI logo

CrewAI

Use Blackbaud MCP with CrewAI

AutoGen logo

AutoGen

Use Blackbaud MCP with AutoGen

FAQ

Frequently asked questions

Start with Blackbaud.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Blackbaud tool your agent needs.Free to start.

Start building