# How to integrate Flutterwave MCP with LlamaIndex

```json
{
  "title": "How to integrate Flutterwave MCP with LlamaIndex",
  "toolkit": "Flutterwave",
  "toolkit_slug": "flutterwave",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/flutterwave/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/flutterwave/framework/llama-index.md",
  "updated_at": "2026-05-06T08:12:08.010Z"
}
```

## Introduction

This guide walks you through connecting Flutterwave to LlamaIndex 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 through natural language commands.
This guide will help you understand how to give your LlamaIndex 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.

## Also integrate Flutterwave with

- [OpenAI Agents SDK](https://composio.dev/toolkits/flutterwave/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/flutterwave/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/flutterwave/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/flutterwave/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/flutterwave/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/flutterwave/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/flutterwave/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/flutterwave/framework/cli)
- [Google ADK](https://composio.dev/toolkits/flutterwave/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/flutterwave/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/flutterwave/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/flutterwave/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/flutterwave/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set your OpenAI and Composio API keys
- Install LlamaIndex and Composio packages
- Create a Composio Tool Router session for Flutterwave
- Connect LlamaIndex to the Flutterwave MCP server
- Build a Flutterwave-powered agent using LlamaIndex
- Interact with Flutterwave through natural language

## What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.
Key features include:
- ReAct Agent: Reasoning and acting pattern for tool-using agents
- MCP Tools: Native support for Model Context Protocol
- Context Management: Maintain conversation context across interactions
- Async Support: Built for async/await patterns

## 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

| Tool slug | Name | Description |
|---|---|---|
| `FLUTTERWAVE_CREATE_BENEFICIARY` | Create Beneficiary | Tool to create a new transfer beneficiary. use when you need to add a beneficiary before making a transfer. |
| `FLUTTERWAVE_CREATE_BULK_VIRTUAL_ACCOUNT_NUMBERS` | Create Bulk Virtual Account Numbers | Tool to create multiple virtual account numbers. use when you need to generate multiple static virtual accounts for customers in a single request. |
| `FLUTTERWAVE_CREATE_PAYMENT_LINK` | Create Payment Link | Tool to create a hosted payment link. use when you need a shareable payment url for one-time transactions. |
| `FLUTTERWAVE_CREATE_PAYMENT_PLAN` | Create Payment Plan | Tool to create a new payment plan. use after confirming plan and customer details. |
| `FLUTTERWAVE_CREATE_SUBACCOUNT` | Create Subaccount | Tool to create a new subaccount. use when you need to configure split disbursement accounts. |
| `FLUTTERWAVE_CREATE_VIRTUAL_ACCOUNT` | Create Virtual Account | Tool to create a new virtual account number. use after confirming customer details when assigning a unique account for bank transfers. |
| `FLUTTERWAVE_DELETE_BENEFICIARY` | Delete Beneficiary | Tool to delete a beneficiary by id. use when you need to remove a saved transfer beneficiary by its unique id after confirming the id. |
| `FLUTTERWAVE_DISABLE_PAYMENT_LINK` | Disable Payment Link | Tool to disable a flutterwave payment link. use when you need to prevent further payments from an existing link after confirming the link is valid. |
| `FLUTTERWAVE_FETCH_BENEFICIARY` | Fetch Beneficiary | Tool to retrieve details of a specific beneficiary by id. use after obtaining a beneficiary id to fetch its full details from flutterwave. |
| `FLUTTERWAVE_FETCH_SUBACCOUNT` | Fetch Subaccount | Tool to retrieve details of a specific subaccount by id. use when you need full subaccount info after creating or updating splits. |
| `FLUTTERWAVE_GENERATE_TRANSACTION_REFERENCE` | Generate Transaction Reference | Tool to generate a unique transaction reference. use when initiating a new flutterwave transaction requires a unique reference to prevent duplication. |
| `FLUTTERWAVE_GET_ALL_SUBSCRIPTIONS` | Get All Subscriptions | Tool to retrieve all subscriptions, including cancelled ones. use when you need a comprehensive list of subscription records for auditing or reporting. |
| `FLUTTERWAVE_GET_ALL_TRANSACTIONS` | Retrieve all transactions | Tool to retrieve a list of all transactions with optional filters. use when you need to paginate or filter transaction history after confirming valid api credentials. |
| `FLUTTERWAVE_GET_ALL_WALLET_BALANCES` | Get All Wallet Balances | Tool to retrieve all wallet balances across currencies. use when reconciling balances after authentication. |
| `FLUTTERWAVE_GET_BALANCES_PER_CURRENCY` | Get Balances per Currency | Tool to retrieve wallet balance for a specific currency. use after transactions to confirm available and ledger balances in a given currency. |
| `FLUTTERWAVE_GET_BILL_CATEGORIES` | Get Bill Categories | Tool to retrieve available bill categories. use after authenticating to flutterwave to display bill payment options to users. |
| `FLUTTERWAVE_GET_MULTIPLE_REFUND_TRANSACTIONS` | Get Multiple Refund Transactions | Tool to retrieve multiple refund transactions with optional filters. use when you need to fetch paginated refund data after confirming valid api credentials. |
| `FLUTTERWAVE_GET_PAYMENT_PLANS` | Get Payment Plans | Tool to retrieve a list of all payment plans. use when you need to fetch and present your account’s configured billing plans. |
| `FLUTTERWAVE_GET_TRANSACTION` | Get Transaction | Tool to retrieve details of a specific transaction by id. use after obtaining the transaction id to fetch its details from flutterwave. |
| `FLUTTERWAVE_GET_TRANSACTION_FEE` | Get Transaction Fee | Tool to retrieve the fee for a specific transaction. use when you need to calculate the total charge including fees before initiating the transaction. |
| `FLUTTERWAVE_GET_TRANSFER_FEE` | Get Transfer Fee | Tool to retrieve the fee for initiating a transfer. use when you need to estimate transfer costs before creating a transfer. example: "calculate the fee for transferring ngn 5000 to an account." |
| `FLUTTERWAVE_INITIATE_MOBILE_MONEY_TANZANIA` | Initiate Mobile Money Tanzania | Tool to initiate a mobile money payment in tanzania. use after collecting customer details to charge via tanzanian mobile money networks. |
| `FLUTTERWAVE_LIST_ALL_BENEFICIARIES` | List All Beneficiaries | Tool to list all saved beneficiaries. use when you need to retrieve all transfer beneficiaries associated with your account. |
| `FLUTTERWAVE_VIEW_TRANSACTION_TIMELINE` | View Transaction Timeline | Tool to retrieve the event timeline for a transaction. use after obtaining the transaction id to audit or track the sequence of events. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Flutterwave MCP server is an implementation of the Model Context Protocol that connects your AI agent to Flutterwave. It provides structured and secure access so your agent can perform Flutterwave operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before you begin, make sure you have:
- Python 3.8/Node 16 or higher installed
- A Composio account with the API key
- An OpenAI API key
- A Flutterwave account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Flutterwave

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

```typescript
npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv
```

### 3. Set environment variables

Create a .env file in your project root:
These credentials will be used to:
- Authenticate with OpenAI's GPT-5 model
- Connect to Composio's Tool Router
- Identify your Composio user session for Flutterwave access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")
```

```typescript
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");
```

### 6. Create a Tool Router session and build the agent function

What's happening here:
- We create a Composio client using your API key and configure it with the LlamaIndex provider
- We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, flutterwave)
- The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
- LlamaIndex will connect to this endpoint to dynamically discover and use the available Flutterwave tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["flutterwave"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Flutterwave actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Flutterwave actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["flutterwave"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Flutterwave actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}
```

### 8. Define the main entry point

What's happening here:
- We're orchestrating the entire application flow
- The agent gets built with proper error handling
- Then we kick off the interactive chat loop so you can start talking to Flutterwave
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Flutterwave, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["flutterwave"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Flutterwave actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Flutterwave actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["flutterwave"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Flutterwave actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();
```

## Conclusion

You've successfully connected Flutterwave to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Flutterwave tools through an MCP endpoint
- LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
- The agent becomes more capable without increasing prompt size
- Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

## How to build Flutterwave MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/flutterwave/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/flutterwave/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/flutterwave/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/flutterwave/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/flutterwave/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/flutterwave/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/flutterwave/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/flutterwave/framework/cli)
- [Google ADK](https://composio.dev/toolkits/flutterwave/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/flutterwave/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/flutterwave/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/flutterwave/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/flutterwave/framework/crew-ai)

## Related Toolkits

- [Stripe](https://composio.dev/toolkits/stripe) - Stripe is a global online payments platform offering APIs for managing payments, customers, and subscriptions. Trusted by businesses for secure, efficient, and scalable payment processing worldwide.
- [Alpha vantage](https://composio.dev/toolkits/alpha_vantage) - Alpha Vantage is a financial data platform offering real-time and historical stock market APIs. Get instant, reliable access to equities, forex, and technical analysis data for smarter trading decisions.
- [Altoviz](https://composio.dev/toolkits/altoviz) - Altoviz is a cloud-based billing and invoicing platform for businesses. It streamlines online payments, expense tracking, and customizable invoice management.
- [Benzinga](https://composio.dev/toolkits/benzinga) - Benzinga provides real-time financial news and data APIs for market coverage. It helps you track breaking news and actionable market insights instantly.
- [Brex](https://composio.dev/toolkits/brex) - Brex provides corporate credit cards and spend management tailored for startups and tech businesses. It helps optimize company cash flow, streamline accounting, and accelerate business growth.
- [Chaser](https://composio.dev/toolkits/chaser) - Chaser is accounts receivable automation software that sends invoice reminders and helps businesses get paid faster. It streamlines the collections process to save time and improve cash flow.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Coinbase](https://composio.dev/toolkits/coinbase) - Coinbase is a platform for buying, selling, and storing cryptocurrency. It makes exchanging and managing crypto simple and secure for everyone.
- [Coinranking](https://composio.dev/toolkits/coinranking) - Coinranking is a comprehensive cryptocurrency market data platform offering access to real-time coin prices, market caps, and historical data. Get accurate, up-to-date stats for thousands of digital assets in one place.
- [Coupa](https://composio.dev/toolkits/coupa) - Coupa is a business spend management platform for procurement, invoicing, and expenses. It helps organizations streamline purchasing, control costs, and gain complete visibility over financial operations.
- [CurrencyScoop](https://composio.dev/toolkits/currencyscoop) - CurrencyScoop is a developer-friendly API for real-time and historical currency exchange rates. Easily access fiat and crypto data for smart, up-to-date financial applications.
- [Daffy](https://composio.dev/toolkits/daffy) - Daffy is a modern charitable giving platform with a donor-advised fund. Easily set aside funds, grow them tax-free, and donate to over 1.7 million U.S. charities.
- [Eagle doc](https://composio.dev/toolkits/eagle_doc) - Eagle doc is an AI-powered OCR API for invoices and receipts. It delivers fast, reliable, and accurate document data extraction for seamless automation.
- [Elorus](https://composio.dev/toolkits/elorus) - Elorus is an online invoicing and time-tracking software for freelancers and small businesses. Easily manage finances, bill clients, and track work in one place.
- [Eodhd apis](https://composio.dev/toolkits/eodhd_apis) - Eodhd apis delivers comprehensive financial data, including live and historical stock prices, via robust APIs. Easily access reliable, up-to-date market insights to power your apps, dashboards, and analytics.
- [Fidel api](https://composio.dev/toolkits/fidel_api) - Fidel api is a secure platform for linking payment cards to web and mobile apps. It enables real-time card transaction monitoring and event-based automation for businesses.
- [Finage](https://composio.dev/toolkits/finage) - Finage is a secure API platform delivering real-time and historical financial data for stocks, forex, crypto, indices, and commodities. It empowers developers and businesses to access, analyze, and act on market data instantly.
- [Finmei](https://composio.dev/toolkits/finmei) - Finmei is an invoicing tool that simplifies billing, invoice management, and expense tracking. Ideal for automating and organizing your business finances in one place.
- [Fixer](https://composio.dev/toolkits/fixer) - Fixer is a currency data API offering real-time and historical exchange rates for 170 currencies. Instantly access accurate, up-to-date forex data for your applications and workflows.
- [Fixer io](https://composio.dev/toolkits/fixer_io) - Fixer.io is a lightweight API for real-time and historical foreign exchange rates. It makes global currency conversion fast, accurate, and hassle-free.

## Frequently Asked Questions

### 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 LlamaIndex?

Yes, you can. LlamaIndex 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.

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