How to integrate Flutterwave MCP with CrewAI

BOOK A CALLGET STARTED FOR FREE
Framework Integration Gradient
Flutterwave Logo
CrewAI Logo
divider

Introduction

This guide walks you through connecting Flutterwave to CrewAI using the Composio tool router. By the end, you'll have a working Flutterwave agent that can create a payment link for a new order, generate virtual account numbers for customers, fetch details of a specific subaccount, disable an existing payment link after use through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Flutterwave account through Composio's Flutterwave 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 a Composio API key and configure your Flutterwave connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Flutterwave
  • Build a conversational loop where your agent can execute Flutterwave operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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

The Flutterwave MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Flutterwave account. It provides structured and secure access to your payment infrastructure, so your agent can perform actions like creating payment links, managing beneficiaries, setting up virtual accounts, and handling subaccounts on your behalf.

  • Instant payment link creation: Let your agent generate hosted payment URLs for one-time or recurring transactions, making it easy to collect payments from customers.
  • Beneficiary management: Add, fetch, or remove transfer beneficiaries directly through your agent, streamlining the process of managing who receives your payouts.
  • Virtual account generation: Automatically create single or bulk virtual bank accounts for customers, enabling seamless and trackable bank transfers.
  • Subaccount setup and retrieval: Have your agent create, configure, or fetch subaccounts to manage split payments and disbursements for complex business needs.
  • Payment link control: Disable active payment links when necessary to prevent further transactions, ensuring you stay in control of your payment flows.

Supported Tools & Triggers

Tools
Create BeneficiaryTool to create a new transfer beneficiary.
Create Bulk Virtual Account NumbersTool to create multiple virtual account numbers.
Create Payment LinkTool to create a hosted payment link.
Create Payment PlanTool to create a new payment plan.
Create SubaccountTool to create a new subaccount.
Create Virtual AccountTool to create a new virtual account number.
Delete BeneficiaryTool to delete a beneficiary by id.
Disable Payment LinkTool to disable a flutterwave payment link.
Fetch BeneficiaryTool to retrieve details of a specific beneficiary by id.
Fetch SubaccountTool to retrieve details of a specific subaccount by id.
Generate Transaction ReferenceTool to generate a unique transaction reference.
Get All SubscriptionsTool to retrieve all subscriptions, including cancelled ones.
Retrieve all transactionsTool to retrieve a list of all transactions with optional filters.
Get All Wallet BalancesTool to retrieve all wallet balances across currencies.
Get Balances per CurrencyTool to retrieve wallet balance for a specific currency.
Get Bill CategoriesTool to retrieve available bill categories.
Get Multiple Refund TransactionsTool to retrieve multiple refund transactions with optional filters.
Get Payment PlansTool to retrieve a list of all payment plans.
Get TransactionTool to retrieve details of a specific transaction by id.
Get Transaction FeeTool to retrieve the fee for a specific transaction.
Get Transfer FeeTool to retrieve the fee for initiating a transfer.
Initiate Mobile Money TanzaniaTool to initiate a mobile money payment in tanzania.
List All BeneficiariesTool to list all saved beneficiaries.
View Transaction TimelineTool to retrieve the event timeline for a transaction.

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:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Flutterwave connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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.

Install dependencies

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Flutterwave via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Flutterwave MCP URL

Create a Composio Tool Router session for Flutterwave

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["flutterwave"],
)
url = session.mcp.url
What's happening:
  • You create a Flutterwave only session through Composio
  • Composio returns an MCP HTTP URL that exposes Flutterwave tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Flutterwave Assistant",
    goal="Help users interact with Flutterwave through natural language commands",
    backstory=(
        "You are an expert assistant with access to Flutterwave tools. "
        "You can perform various Flutterwave operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Flutterwave MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Flutterwave operations.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Flutterwave related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_flutterwave_agent.py

Complete Code

Here's the complete code to get you started with Flutterwave and CrewAI:

python
# file: crewai_flutterwave_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Flutterwave session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["flutterwave"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Flutterwave assistant agent
    toolkit_agent = Agent(
        role="Flutterwave Assistant",
        goal="Help users interact with Flutterwave through natural language commands",
        backstory=(
            "You are an expert assistant with access to Flutterwave tools. "
            "You can perform various Flutterwave operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Flutterwave operations.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Flutterwave related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Flutterwave through Composio's Tool Router. The agent can perform Flutterwave operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Flutterwave MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Flutterwave MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Flutterwave MCP with Claude Agent SDK

Google ADK

Google ADK

Use Flutterwave MCP with Google ADK

LangChain

LangChain

Use Flutterwave MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Flutterwave MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Flutterwave MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Flutterwave MCP with LlamaIndex

FAQ

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

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

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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 Flutterwave tools.

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

Yes, absolutely. You can configure which Flutterwave 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 Flutterwave data and credentials are handled as safely as possible.

Used by agents from

Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Book a call↗Get started for free