# How to integrate Postalytics MCP with LlamaIndex

```json
{
  "title": "How to integrate Postalytics MCP with LlamaIndex",
  "toolkit": "Postalytics",
  "toolkit_slug": "postalytics",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/postalytics/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/postalytics/framework/llama-index.md",
  "updated_at": "2026-03-29T06:46:11.008Z"
}
```

## Introduction

This guide walks you through connecting Postalytics to LlamaIndex using the Composio tool router. By the end, you'll have a working Postalytics agent that can create a new direct mail campaign, sync contacts from hubspot to postalytics, track delivery status for recent campaigns through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Postalytics account through Composio's Postalytics MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Postalytics with

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

The Postalytics MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Postalytics account. It provides structured and secure access so your agent can perform Postalytics operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `POSTALYTICS_ADD_ACCOUNT` | Add Account | Tool to create a new sub-account in the Postalytics system. Use when you need to create a new account with a unique ID associated with the requester's user ID as parent. The response includes the API key and user ID for the new account, which should be stored for future API calls. |
| `POSTALYTICS_ADD_CONTACT` | Add Contact | Tool to add a contact to a specified contact list with their information. Use when you need to create a new contact or update an existing one on a contact list. |
| `POSTALYTICS_CREATE_NEW_CAMPAIGN` | Create New Campaign | Tool to create a new direct mail campaign in Postalytics. Use when you need to start a new campaign with specified sender details and template. Important: A template must be created and proofed before creating the campaign. |
| `POSTALYTICS_CREATE_SUPPRESSION_LIST` | Create Suppression List | Tool to create a new suppression list that can be used in campaigns to suppress contacts from being sent mail. Use when you need to create an empty suppression list. Note that contacts must be added separately using the SuppressionListContact API after the list is created. |
| `POSTALYTICS_CREATE_SUPPRESSION_LIST_CONTACT` | Create Suppression List Contact | Tool to create a new suppression contact on a specified suppression list. Use when you need to add a contact to a suppression list to prevent them from receiving mailings. |
| `POSTALYTICS_CREATE_TEMPLATE` | Create Template | Tool to create a new template with full HTML for postcard or letter. Use when you need to create a template by providing complete HTML markup or image URLs for front/back. The template can be used for various mail types including postcards, letters, and bifolds. |
| `POSTALYTICS_CREATE_WEBHOOK` | Create Webhook | Tool to create a new webhook to receive campaign event notifications from Postalytics. Use when you need to set up a webhook endpoint that will be notified about campaign events like sent, delivered, opened, or clicked. |
| `POSTALYTICS_DELETE_ACCOUNT` | Delete Account | Tool to delete a Postalytics account and all associated campaigns, templates, and lists. Use when you need to permanently remove a sub account or sub user account. Cannot delete parent accounts. |
| `POSTALYTICS_DELETE_CAMPAIGN` | Delete Campaign | Tool to delete a campaign from the system. Use when you need to remove a campaign that is no longer needed. |
| `POSTALYTICS_DELETE_SUPPRESSION_LIST` | Delete Suppression List | Tool to delete a specified suppression list. Use when you need to remove a suppression list that is no longer needed. |
| `POSTALYTICS_DELETE_SUPPRESSION_LIST_CONTACT` | Delete Suppression List Contact | Tool to delete a specific contact from a suppression list. Use when you need to remove a contact from a suppression list in Postalytics. |
| `POSTALYTICS_GET_ALL_CONTACT_LISTS` | Get All Contact Lists | Tool to retrieve all contact lists for an account. Use when you need to get a complete list of contact lists including their IDs, names, item counts, and creation dates. |
| `POSTALYTICS_GET_ALL_CONTACTS_ON_A_LIST` | Get All Contacts on a List | Tool to retrieve all contacts from a specified contact list with pagination support. Use when you need to get contacts from a list, with optional pagination using start offset and limit parameters. |
| `POSTALYTICS_GET_ALL_DRIP_CAMPAIGNS` | Get All Drip Campaigns | Tool to retrieve all triggered drip campaign names and endpoint IDs in the account. Use when you need to list all available drip campaigns for the authenticated user. |
| `POSTALYTICS_GET_ALL_FLOWS` | Get All Flows | Tool to retrieve all flows for the requester's account. Use when you need to list or browse available flows. |
| `POSTALYTICS_GET_ALL_WEBHOOKS` | Get All Webhooks | Tool to retrieve all webhooks configured for the authenticated account. Use when you need to view webhook configurations for campaigns. |
| `POSTALYTICS_GET_INTEGRATIONS` | Get Integrations | Tool to retrieve all Connect integrations configured for the authenticated user's account. Use when you need to view CRM or data source integrations. |
| `POSTALYTICS_GET_MY_ACCOUNT` | Get My Account | Tool to retrieve basic account information for the authenticated user. Use when you need to get account details such as contact information, address, or API key. |
| `POSTALYTICS_GET_SUPPRESSION_LIST` | Get Suppression List | Tool to get the details of a suppression list based on the id supplied. Use when you need to retrieve information about a specific suppression list. |
| `POSTALYTICS_GET_SUPPRESSION_LIST_CONTACT` | Get Suppression List Contact | Tool to retrieve a specific contact from a suppression list. Use when you need to get details about a contact on a specific suppression list by their list ID and contact ID. |
| `POSTALYTICS_GET_SUPPRESSION_LIST_CONTACTS` | Get Suppression List Contacts | Tool to get all contacts on a specified suppression list. Use when you need to retrieve contacts that are suppressed for a particular list. |
| `POSTALYTICS_GET_SUPPRESSION_LISTS` | Get Suppression Lists | Tool to retrieve all suppression lists for the authenticated user. Use when you need to view or manage suppression lists. Returns all lists or a specific list when ID is provided. |
| `POSTALYTICS_UPDATE_ACCOUNT` | Update Account | Tool to update an existing account in the Postalytics system. Use when you need to modify account information such as contact details, address, or credentials for an existing account. |
| `POSTALYTICS_UPDATE_SUPPRESSION_LIST_CONTACT` | Update Suppression List Contact | Tool to update a suppression contact on the specified suppression list. Use when you need to modify contact information for a specific contact on a suppression list. |

## Supported Triggers

None listed.

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

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

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

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 Postalytics 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, postalytics)
- 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 Postalytics 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=["postalytics"],
    )

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

  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 Postalytics 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 Postalytics
```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 Postalytics, 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=["postalytics"],
    )

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

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

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

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- [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease.
- [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic.
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- [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere.
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- [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools.
- [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes.
- [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management.
- [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals.
- [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams.
- [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience.
- [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs.
- [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics.

## Frequently Asked Questions

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

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

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

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

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