# How to integrate Sendfox MCP with LlamaIndex

```json
{
  "title": "How to integrate Sendfox MCP with LlamaIndex",
  "toolkit": "Sendfox",
  "toolkit_slug": "sendfox",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/sendfox/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/sendfox/framework/llama-index.md",
  "updated_at": "2026-05-12T10:25:16.583Z"
}
```

## Introduction

This guide walks you through connecting Sendfox to LlamaIndex using the Composio tool router. By the end, you'll have a working Sendfox agent that can list all active campaigns this week, unsubscribe a contact by email address, retrieve all contacts from your main list through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Sendfox account through Composio's Sendfox MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Sendfox with

- [OpenAI Agents SDK](https://composio.dev/toolkits/sendfox/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/sendfox/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/sendfox/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/sendfox/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/sendfox/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/sendfox/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/sendfox/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/sendfox/framework/cli)
- [Google ADK](https://composio.dev/toolkits/sendfox/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/sendfox/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/sendfox/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/sendfox/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/sendfox/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 Sendfox
- Connect LlamaIndex to the Sendfox MCP server
- Build a Sendfox-powered agent using LlamaIndex
- Interact with Sendfox 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 Sendfox MCP server, and what's possible with it?

The Sendfox MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Sendfox account. It provides structured and secure access to your contact lists, campaigns, automations, and more, so your agent can fetch contacts, manage lists, retrieve campaign data, and automate subscriber actions on your behalf.
- Contact management and lookup: Instantly retrieve contact details by email or ID, fetch all contacts, or discover specific fields to personalize your outreach.
- List organization and updates: Ask your agent to fetch all your Sendfox lists, get details for a specific list, or remove contacts from lists as needed.
- Campaign and automation insights: Effortlessly retrieve paginated lists of campaigns or automations, so you can stay on top of your email marketing performance.
- Subscription and unsubscribe actions: Let your agent globally unsubscribe a contact or handle opt-outs automatically for better list hygiene.
- Discover contact field metadata: Pull all available contact fields to help with dynamic contact creation or targeted updates.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SENDFOX_DELETE_CONTACT_FROM_LIST` | Delete Contact from List | Tool to remove a contact from a specific list in SendFox. Use when you need to disassociate a contact from a list without deleting the contact entirely. The contact will remain in your account but will no longer be a member of the specified list. |
| `SENDFOX_GET_AUTOMATIONS` | Get Automations | Tool to retrieve a list of automations. Use when you need to list all automations for your SendFox account. |
| `SENDFOX_GET_CAMPAIGN_BY_ID` | Get Campaign by ID | Retrieve details for a specific campaign by its ID from SendFox. Use this when you need to fetch information about a particular campaign. Returns campaign details including title, subject, HTML content, sender info, and scheduling details. |
| `SENDFOX_GET_CAMPAIGNS` | Get Campaigns | Retrieve a paginated list of email campaigns from SendFox. Use this to fetch all campaigns or navigate through pages of results. Returns campaign details including status, subject, content, and timestamps. |
| `SENDFOX_GET_CONTACT_BY_ID` | Get Contact by ID | Retrieves a contact's details by their unique ID from SendFox. Use this tool when you need to look up a specific contact's information after obtaining their ID from a contact list or other API response. Returns contact details including email, name, subscription status, and list memberships. |
| `SENDFOX_GET_CONTACT_FIELDS` | Get Contact Fields | Retrieves all contact fields available in the SendFox account. Use this to discover available fields before creating or updating contacts. Returns standard fields (email, first_name, last_name) and any custom fields configured in the account. |
| `SENDFOX_GET_CONTACTS` | Get Contacts | Tool to retrieve a paginated list of contacts. Use when you need to fetch contacts in pages, optionally filtering by email. |
| `SENDFOX_GET_CONTACTS_IN_LIST` | Get Contacts in List | Tool to retrieve contacts in a specific list. Use when you need to fetch all contacts belonging to a particular list, optionally filtering by search query. |
| `SENDFOX_GET_CURRENT_USER` | Get Current User | Tool to retrieve information about the authenticated user from SendFox. Returns user details including name, email, contact count, and contact limit. Use this tool when you need to check account information or verify authentication status. |
| `SENDFOX_GET_FORMS` | Get Forms | Tool to retrieve a paginated list of forms from SendFox. Use when you need to fetch all forms or search for specific forms by query. |
| `SENDFOX_GET_LIST_BY_ID` | Get List by ID | Retrieves details of a specific contact list by its ID from SendFox. Use this tool when you need information about a particular list (name, contact count, timestamps). Requires a valid list_id which can be obtained from the 'Get Lists' action. |
| `SENDFOX_GET_LISTS` | Get Lists | Retrieve all contact lists from your SendFox account with pagination support. Use this tool when you need to: - Fetch all available contact lists for your account - Get list IDs to use with other SendFox actions (e.g., adding contacts to lists) - Check list names and browse through paginated results Returns a list of contact lists with their IDs and names, along with pagination metadata. |
| `SENDFOX_LIST_CONTACT_FIELDS` | List Contact Fields | Tool to list all custom contact fields defined by the user. Returns a paginated list of contact fields with their IDs, names, and timestamps. |
| `SENDFOX_LIST_UNSUBSCRIBED_CONTACTS` | List Unsubscribed Contacts | Tool to retrieve a paginated list of contacts who have unsubscribed. Use when you need to fetch unsubscribed contacts, optionally filtering by search query. |
| `SENDFOX_PATCH_UNSUBSCRIBE_CONTACT` | Unsubscribe Contact | Unsubscribe a contact from all email communications in your SendFox account. Use this tool when you need to: - Globally unsubscribe a contact from all future emails - Honor unsubscribe requests from subscribers - Mark a contact as opted-out The contact will be marked as unsubscribed but remains in your contacts database. This is a permanent action - the contact will not receive any future campaigns. |
| `SENDFOX_POST_CREATE_CONTACT` | Create Contact | Create a new contact (subscriber) in your SendFox account. Use this tool when you need to: - Add a new subscriber to your email list - Create a contact with optional first/last name - Add a contact to one or more specific lists If the contact already exists, their information will be updated with the provided data. |
| `SENDFOX_POST_CREATE_LIST` | Create List | Create a new contact list in your SendFox account. Use this tool when you need to: - Create a new mailing list for organizing contacts - Set up a list before adding subscribers to it - Segment your audience by creating topic-specific lists The list will be created with 0 contacts initially. After creation, use other SendFox actions to add contacts to this list. Returns the created list's ID, name, and metadata. |

## Supported Triggers

None listed.

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

The Sendfox MCP server is an implementation of the Model Context Protocol that connects your AI agent to Sendfox. It provides structured and secure access so your agent can perform Sendfox 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 Sendfox account and project
- Basic familiarity with async Python/Typescript

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

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 Sendfox 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, sendfox)
- 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 Sendfox 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=["sendfox"],
    )

    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 Sendfox actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Sendfox 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: ["sendfox"],
    },
  );

  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 Sendfox 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 Sendfox
```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 Sendfox, 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=["sendfox"],
    )

    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 Sendfox actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Sendfox 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: ["sendfox"],
    },
  );

  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 Sendfox 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 Sendfox to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Sendfox 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 Sendfox MCP Agent with another framework

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

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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Sendfox MCP?

With a standalone Sendfox MCP server, the agents and LLMs can only access a fixed set of Sendfox tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Sendfox 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 Sendfox tools.

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

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

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