How to integrate Givebutter MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Givebutter to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Givebutter agent that can create a new fundraising campaign for our school, list all recent payouts to our nonprofit account, get details for fund with id fund_abc123, retrieve all members of the summer gala campaign through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Givebutter account through Composio's Givebutter MCP server.

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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Givebutter
  • Configure an AI agent that can use Givebutter as a tool
  • Run a live chat session where you can ask the agent to perform Givebutter operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

The Givebutter MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Givebutter account. It provides structured and secure access to your fundraising platform, so your agent can perform actions like creating campaigns, tracking donations, managing contacts, and handling payouts on your behalf.

  • Campaign management and creation: Easily instruct your agent to start new fundraising campaigns, update campaign details, or remove old campaigns when needed.
  • Donation and payout tracking: Ask your agent to retrieve lists of payouts, monitor donation flows, and keep tabs on your fundraising progress in real time.
  • Contact and member administration: Let your agent add, archive, or delete contacts, and fetch lists of campaign members for smooth supporter management.
  • Fund and webhook operations: Direct your agent to get details about specific funds, create or remove webhooks for event notifications, and manage fundraising infrastructure automatically.
  • Automated data cleanup: Empower your agent to archive or delete obsolete contacts, funds, or webhooks, keeping your Givebutter account organized and up to date.

Supported Tools & Triggers

Tools
Archive ContactTool to archive a contact by their id.
Create CampaignTool to create a new campaign.
Create WebhookTool to create a new webhook subscription.
Delete CampaignTool to delete a campaign by its id.
Delete ContactTool to delete a contact by their id.
Delete FundTool to delete a fund by its id.
Delete WebhookTool to delete a webhook by its id.
Get FundTool to retrieve details of a specific fund by its id.
Get MembersTool to retrieve a paginated list of members for a given campaign.
Get PayoutsTool to retrieve a list of payouts associated with your account.
Get PlansTool to retrieve a list of plans associated with your account.
Get TeamsTool to retrieve a list of teams for a specific campaign.
Get TicketsTool to retrieve a list of tickets.
Get TransactionsTool to retrieve a list of transactions associated with your account.
Get WebhooksTool to retrieve all webhooks configured for your account.
Update CampaignTool to update an existing campaign's details by its id.
Update ContactTool to update an existing contact's details by contact id.
Update WebhookTool to update an existing webhook subscription's details.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Givebutter project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Givebutter.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Givebutter Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["givebutter"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only givebutter.
  • The router checks the user's Givebutter connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Givebutter.
  • This approach keeps things lightweight and lets the agent request Givebutter tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Givebutter. "
        "Help users perform Givebutter operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Givebutter and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Givebutter operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Givebutter.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Givebutter and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["givebutter"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Givebutter. "
        "Help users perform Givebutter operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Givebutter MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Givebutter.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Givebutter MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Givebutter MCP with Claude Agent SDK

Google ADK

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Use Givebutter MCP with Google ADK

LangChain

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Use Givebutter MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Givebutter MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Givebutter MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Givebutter MCP with LlamaIndex

CrewAI

CrewAI

Use Givebutter MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Givebutter MCP?

With a standalone Givebutter MCP server, the agents and LLMs can only access a fixed set of Givebutter tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Givebutter and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Givebutter tools.

Can I manage the permissions and scopes for Givebutter while using Tool Router?

Yes, absolutely. You can configure which Givebutter scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Givebutter data and credentials are handled as safely as possible.

Used by agents from

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