# How to integrate Semrush MCP with LlamaIndex

```json
{
  "title": "How to integrate Semrush MCP with LlamaIndex",
  "toolkit": "Semrush",
  "toolkit_slug": "semrush",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/semrush/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/semrush/framework/llama-index.md",
  "updated_at": "2026-05-06T08:27:20.223Z"
}
```

## Introduction

This guide walks you through connecting Semrush to LlamaIndex using the Composio tool router. By the end, you'll have a working Semrush agent that can show top anchor texts for example.com, compare backlink profiles for three domains, get keyword overview for 'organic coffee' through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Semrush account through Composio's Semrush MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Semrush with

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

The Semrush MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Semrush account. It provides structured and secure access to your SEO, keyword, and advertising analytics, so your agent can perform actions like keyword research, competitor analysis, backlink audits, and ad copy retrieval automatically on your behalf.
- Comprehensive keyword research and reporting: Let your agent fetch broad match keywords, generate batch keyword overviews, and analyze key SEO metrics like search volume and difficulty in real time.
- Competitor and backlink analysis: Ask your agent to pull backlink profiles, perform batch comparisons of domains, and summarize backlink authority and link types for competitive intelligence.
- Ad campaign and copy insights: Have the agent retrieve unique Google Ads copies for any domain, helping you benchmark and optimize your own ad strategies based on real competitor data.
- Content and category profiling: Enable your agent to analyze and categorize domains or URLs, surfacing topic strengths and audience focus areas for smarter content planning.
- Anchor text and authority monitoring: Direct your agent to report on anchor text distributions and authority score profiles, giving you actionable insights for improving link-building efforts.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SEMRUSH_ADS_COPIES` | Get ad copies | Retrieves unique ad copies semrush has observed for a specified domain from a regional database, detailing ads seen in google's paid search results. |
| `SEMRUSH_ANCHORS` | Get anchor texts | Use this action to get a csv report of anchor texts for backlinks pointing to a specified, publicly accessible domain, root domain, or url. |
| `SEMRUSH_AUTHORITY_SCORE_PROFILE` | Get authority score profile | Retrieves the authority score (as) profile for a specified target, showing the count of referring domains that link to the target for each as value from 0 to 100. |
| `SEMRUSH_BACKLINKS` | Get backlinks | Fetches backlinks for a specified domain or url as a csv-formatted string, allowing customization of columns, sorting, and filtering; ensure `display limit` surpasses `display offset` when an offset is used, and note the `urlanchor` filter may have limitations for targets with extensive backlinks. |
| `SEMRUSH_BACKLINKS_OVERVIEW` | Backlinks overview | Provides a csv-formatted summary of backlinks, including authority score and link type breakdowns, for a specified and publicly accessible domain, root domain, or url. |
| `SEMRUSH_BATCH_COMPARISON` | Batch comparison | Compares backlink profiles for multiple specified targets (domains, subdomains, or urls) to analyze and compare link-building efforts. |
| `SEMRUSH_BATCH_KEYWORD_OVERVIEW` | Batch keyword overview | Fetches a keyword overview report from a semrush regional database for up to 100 keywords, providing metrics like search volume, cpc, and keyword difficulty. |
| `SEMRUSH_BROAD_MATCH_KEYWORD` | Broad match keyword | Fetches broad match keywords for a given phrase; `display sort` and `display filter` parameters are defined but currently not utilized by the api call. |
| `SEMRUSH_CATEGORIES` | Get categories | Retrieves categories and their 0-1 confidence ratings for a specified domain, subdomain, or url, with results sorted by rating. |
| `SEMRUSH_CATEGORIES_PROFILE` | Get categories profile | Retrieves a profile of content categories from referring domains for a specified target, analyzing its first 10,000 referring domains and sorting results by domain count. |
| `SEMRUSH_COMPETITORS` | Get competitor data | Retrieves a customizable csv report of competitors for a specified target (root domain, domain, or url) based on shared backlinks or referring domains, ensuring the target is valid and its type is correctly specified. |
| `SEMRUSH_COMPETITORS_IN_ORGANIC_SEARCH` | Get competitors in organic search | Use to get a domain's organic search competitors from semrush as a semicolon-separated string; `display date` requires 'yyyymm15' format if used. |
| `SEMRUSH_COMPETITORS_IN_PAID_SEARCH` | Get competitors in paid search | Retrieves a list of a domain's competitors in paid search results from a specified regional database. |
| `SEMRUSH_DOMAIN_AD_HISTORY` | Get domain ad history | Retrieves a domain's 12-month advertising history from semrush (keywords bid on, ad positions, ad copy) for ppc strategy and competitor analysis; most effective when the domain has ad history in the selected database. |
| `SEMRUSH_DOMAIN_ORGANIC_PAGES` | Get domain organic pages | Fetches a report on a domain's unique organic pages ranking in google's top 100 search results, with options for specifying database, date, columns, sorting, and filtering. |
| `SEMRUSH_DOMAIN_ORGANIC_SEARCH_KEYWORDS` | Get domain organic search keywords | Retrieves organic search keywords for a domain from a specified semrush regional database; `display positions` must be set if `display daily=1` for daily updates. |
| `SEMRUSH_DOMAIN_ORGANIC_SUBDOMAINS` | Get domain organic subdomains | Retrieves a report on subdomains of a given domain that rank in google's top 100 organic search results for a specified regional database. |
| `SEMRUSH_DOMAIN_PAID_SEARCH_KEYWORDS` | Get domain paid search keywords | Fetches keywords driving paid search traffic to a specified, existing domain using a supported semrush regional database. |
| `SEMRUSH_DOMAIN_PLA_SEARCH_KEYWORDS` | Get PLA search keywords for a domain | Retrieves product listing ad (pla) search keywords for a specified domain from a semrush regional database. |
| `SEMRUSH_DOMAIN_VS_DOMAIN` | Compare domains | Analyzes keyword rankings by comparing up to five domains to find common, unique, or gap keywords, using specified organic/paid types and comparison logic in the `domains` string. |
| `SEMRUSH_HISTORICAL_DATA` | Get historical data | Retrieves monthly historical backlink and referring domain data for a specified root domain, returned as a time series string with newest records first. |
| `SEMRUSH_INDEXED_PAGES` | Get indexed pages | Retrieves a list of indexed pages from semrush for a specified `target` (root domain, domain, or url) and `target type`, ensuring `target` is publicly accessible, semrush-analyzable, and correctly matches `target type`. |
| `SEMRUSH_KEYWORD_DIFFICULTY` | Get keyword difficulty | Determines the keyword difficulty (kd) score (0-100, higher means greater difficulty) for a given phrase in a specific semrush regional database to assess its seo competitiveness. |
| `SEMRUSH_KEYWORD_OVERVIEW_ALL_DATABASES` | Keyword overview all databases | Fetches a keyword overview from semrush for a specified phrase, including metrics like search volume, cpc, and competition. |
| `SEMRUSH_KEYWORD_OVERVIEW_ONE_DATABASE` | Get keyword overview for one database | Fetches a keyword summary for a specified phrase from a chosen regional database. |
| `SEMRUSH_KEYWORDS_ADS_HISTORY` | Get keywords ads history | Fetches a historical report (last 12 months) of domains advertising on a specified keyword in google ads, optionally for a specific month ('yyyymm15') or the most recent period, returning raw csv-like data. |
| `SEMRUSH_ORGANIC_RESULTS` | Get organic results | Retrieves up to 100,000 domains and urls from google's top 100 organic search results for a keyword and region, returning a raw string; use `display date` in 'yyyymm15' format (day must be '15') for historical data. |
| `SEMRUSH_PAID_RESULTS` | Get paid search results | Fetches domains ranking in google's paid search results (adwords) for a specified keyword and regional database. |
| `SEMRUSH_PHRASE_QUESTIONS` | Phrase questions | Fetches question-format keywords semantically related to a given query phrase for a specified regional database, aiding in understanding user search intent and discovering content ideas. |
| `SEMRUSH_PLA_COMPETITORS` | Get PLA competitors | Retrieves domains competing with a specified domain in google's product listing ads (pla) from a given semrush regional database. |
| `SEMRUSH_PLA_COPIES` | Get PLA copies | Fetches product listing ad (pla) copies that semrush observed for a domain in google's paid search results. |
| `SEMRUSH_REFERRING_DOMAINS` | Get referring domains | Retrieves a report as a text string (e.g., csv) listing domains that link to a target, with options to filter by type (not value). |
| `SEMRUSH_REFERRING_DOMAINS_BY_COUNTRY` | Get referring domains by country | Generates a csv report detailing the geographic distribution of referring domains (by country, determined via ip address) for a specified, publicly accessible target. |
| `SEMRUSH_REFERRING_I_PS` | Referring i ps | Fetches ip addresses that are sources of backlinks for a specified target domain, root domain, or url. |
| `SEMRUSH_RELATED_KEYWORDS` | Find related keywords | Call this to find related keywords (including synonyms and variations) for a target phrase in a specific regional database; `display date` (if used for historical data) must be 'yyyymm15' for a past month. |
| `SEMRUSH_TLD_DISTRIBUTION` | Get TLD distribution | Fetches a report on the top-level domain (tld) distribution of referring domains for a specified target, useful for analyzing geographic or categorical backlink diversity. |

## Supported Triggers

None listed.

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

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

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

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 Semrush 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, semrush)
- 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 Semrush 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=["semrush"],
    )

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

  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 Semrush 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 Semrush
```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 Semrush, 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=["semrush"],
    )

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

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

- [ChatGPT](https://composio.dev/toolkits/semrush/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/semrush/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/semrush/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/semrush/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/semrush/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/semrush/framework/codex)
- [Cursor](https://composio.dev/toolkits/semrush/framework/cursor)
- [VS Code](https://composio.dev/toolkits/semrush/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/semrush/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/semrush/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/semrush/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/semrush/framework/cli)
- [Google ADK](https://composio.dev/toolkits/semrush/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/semrush/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/semrush/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/semrush/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/semrush/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.
- [Google Ads](https://composio.dev/toolkits/googleads) - Google Ads is Google's online advertising platform for creating, managing, and optimizing digital campaigns. It helps businesses reach targeted customers and maximize return on ad spend.
- [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.
- [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 Semrush MCP?

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

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

Yes, absolutely. You can configure which Semrush 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 Semrush 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)