# How to integrate Google Ads MCP with LlamaIndex

```json
{
  "title": "How to integrate Google Ads MCP with LlamaIndex",
  "toolkit": "Google Ads",
  "toolkit_slug": "googleads",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/googleads/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/googleads/framework/llama-index.md",
  "updated_at": "2026-05-06T08:14:10.114Z"
}
```

## Introduction

This guide walks you through connecting Google Ads to LlamaIndex using the Composio tool router. By the end, you'll have a working Google Ads agent that can create a new customer list for holiday campaigns, get campaign details by campaign id, list all current customer lists in your account through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Google Ads account through Composio's Google Ads MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Google Ads with

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

The Google Ads MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Google Ads account. It provides structured and secure access to your advertising data, so your agent can perform actions like creating customer lists, retrieving campaign details, and managing audience segments on your behalf.
- Automated customer list creation: Instantly have your agent create new customer lists for targeted marketing campaigns, streamlining your segmentation workflows.
- Campaign insights by ID or name: Let your agent fetch detailed information for any ad campaign using its ID or name, making reporting and optimization a breeze.
- Customer list management: Ask your agent to retrieve and review all your existing customer lists, so you always know who you're targeting.
- Add or remove contacts from lists: Seamlessly update audience membership by having your agent add or remove contacts from specified customer lists for more dynamic targeting.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GOOGLEADS_CREATE_CUSTOMER_LIST` | Create customer list | Createcustomerlist tool will create a customer list in google ads. |
| `GOOGLEADS_GET_CAMPAIGN_BY_ID` | Get Campaign By Id | Getcampaignbyid tool will return details of a campaign in google ads. |
| `GOOGLEADS_GET_CAMPAIGN_BY_NAME` | Get campaign by name | Getcampaignbyname tool will run a sql getcampaignbyname in google ads. |
| `GOOGLEADS_GET_CUSTOMER_LISTS` | Get customer lists | Getcustomerlists tool will list all customer lists in google ads. |
| `GOOGLEADS_GOOGLEADS_ADD_OR_REMOVE_TO_CUSTOMER_LIST` | Add or remove to customer list | Addorremovetocustomerlist tool will add a contact to a customer list in google ads. note: it takes 6 to 12 hours for changes to be reflected in the customer list. |

## Supported Triggers

None listed.

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

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

### 1. Getting API Keys for OpenAI, Composio, and Google Ads

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 Google Ads 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, google ads)
- 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 Google Ads 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=["googleads"],
    )

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

  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 Google Ads 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 Google Ads
```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 Google Ads, 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=["googleads"],
    )

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

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

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

## Related Toolkits

- [Metaads](https://composio.dev/toolkits/metaads) - Metaads is Meta's official Ads API that lets you manage, analyze, and optimize your Facebook and Instagram ad campaigns. Streamline ad operations and gain deeper insights with robust automation.
- [Adrapid](https://composio.dev/toolkits/adrapid) - Adrapid is a platform for rapid creation of digital marketing visuals using templates. It streamlines design workflows for banners, images, and HTML5 content with automation.
- [Adyntel](https://composio.dev/toolkits/adyntel) - Adyntel is an API that retrieves LinkedIn ads for any company using a domain or LinkedIn Page ID. Easily access competitive ad intelligence to power your marketing workflows.
- [Beaconstac](https://composio.dev/toolkits/beaconstac) - Beaconstac is a platform for creating and managing QR codes and proximity beacons. It helps businesses engage customers and track marketing performance with powerful analytics.
- [Campaign cleaner](https://composio.dev/toolkits/campaign_cleaner) - Campaign cleaner is an email campaign optimization tool that boosts compatibility and deliverability across email clients. It helps marketers get better results by cleaning, enhancing, and ensuring high performance for every campaign.
- [Deadline funnel](https://composio.dev/toolkits/deadline_funnel) - Deadline Funnel lets you create personalized deadlines and timers for your marketing campaigns. It helps marketers boost conversions by adding authentic urgency to offers.
- [Instantly](https://composio.dev/toolkits/instantly) - Instantly is a platform for automating cold email outreach, managing leads, and optimizing deliverability. Get better results from email campaigns with minimal manual effort.
- [Proofly](https://composio.dev/toolkits/proofly) - Proofly is a social proof platform that displays real-time notifications of customer activity on your site. It helps you increase website conversions by building trust and urgency for visitors.
- [Segmetrics](https://composio.dev/toolkits/segmetrics) - Segmetrics is a marketing analytics platform that reveals detailed insights into your customer journeys. It helps businesses optimize marketing strategies with accurate, actionable reporting.
- [Semrush](https://composio.dev/toolkits/semrush) - Semrush is a leading SEO tool suite for keyword research, competitor analysis, and campaign tracking. It empowers marketers to improve search rankings and optimize online visibility.
- [Sendloop](https://composio.dev/toolkits/sendloop) - Sendloop is an all-in-one email marketing platform built for SaaS, e-commerce, and small businesses. It makes it easy to send campaigns, manage lists, and track results—all in one place.
- [Sidetracker](https://composio.dev/toolkits/sidetracker) - Sidetracker is a marketing analytics platform that tracks expenses, sales funnels, and customer journeys. It helps optimize marketing spend and visualize campaign performance from start to finish.
- [Stannp](https://composio.dev/toolkits/stannp) - Stannp is an API-driven direct mail platform for sending postcards and letters programmatically. It lets you automate physical mail delivery—no manual printing or mailing required.
- [Tapfiliate](https://composio.dev/toolkits/tapfiliate) - Tapfiliate is an affiliate and referral tracking platform for businesses. It helps companies efficiently manage, track, and grow their affiliate programs.
- [Tpscheck](https://composio.dev/toolkits/tpscheck) - Tpscheck is a real-time service for verifying UK phone numbers against TPS and CTPS registers. It helps prevent unwanted marketing calls and ensures compliance with UK telemarketing laws.
- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options.
- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Google Ads MCP?

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

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

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

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[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)