How to integrate Semrush MCP with Mastra AI

This guide walks you through connecting Semrush to Mastra AI 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 Mastra AI 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.

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Introduction

This guide walks you through connecting Semrush to Mastra AI 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 Mastra AI 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

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TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Semrush tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Semrush tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Semrush agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Semrush through MCP.
3

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models
5

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session
6

Create a Tool Router session for Semrush

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["semrush"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Semrush MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "semrush" for Semrush access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Semrush toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "semrush-mastra-agent",
    instructions: "You are an AI agent with Semrush tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM
9

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        semrush: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Semrush toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Semrush and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["semrush"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      semrush: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "semrush-mastra-agent",
    instructions: "You are an AI agent with Semrush tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { semrush: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Semrush through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows
TOOLS

Supported Tools

Every Semrush action and event your agent gets out of the box.

Check Semrush account units balance

Tool to fetch the remaining Semrush Standard API units for the authenticated account.

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.

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.

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.

Get backlinks

Fetches backlinks for a specified domain or URL as a semicolon-delimited CSV string (parse with `sep=';'`); allows customization of columns, sorting, and filtering.

Backlinks overview

Provides a semicolon-delimited (sep=';') CSV summary of backlinks, including Authority Score and link type breakdowns, for a specified and publicly accessible domain, root domain, or URL.

Batch comparison

Compares backlink profiles for multiple specified targets (domains, subdomains, or URLs) to analyze and compare link-building efforts.

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.

Broad match keyword

Fetches broad match keywords for a given phrase.

Get categories

Retrieves categories and their 0-1 confidence ratings for a specified domain, subdomain, or URL, with results sorted by rating.

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.

Get competitor data

Retrieves a CSV-formatted report of competitors for a specified target (root domain, domain, or URL) based on shared backlinks or referring domains.

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.

Get competitors in paid search

Retrieves a list of a domain's competitors in paid search results from a specified regional database.

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.

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.

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.

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.

Get domain paid search keywords

Fetches keywords driving paid search traffic to a specified, existing domain using a supported Semrush regional database.

Get PLA search keywords for a domain

Retrieves Product Listing Ad (PLA) search keywords for a specified domain from a Semrush regional database.

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.

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.

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`.

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.

Keyword overview all databases

Fetches a keyword overview from Semrush for a specified phrase, including metrics like search volume, CPC, and competition.

Get keyword overview for one database

Fetches a keyword summary for a specified phrase from a chosen regional database.

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.

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.

Get paid search results

Fetches domains ranking in Google's paid search results (AdWords) for a specified keyword and regional database.

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.

Get PLA competitors

Retrieves domains competing with a specified domain in Google's Product Listing Ads (PLA) from a given Semrush regional database.

Get PLA copies

Fetches Product Listing Ad (PLA) copies that Semrush observed for a domain in Google's paid search results.

Get referring domains

Retrieves a semicolon-delimited text report listing domains that link to a target, with options to filter by type (not value).

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.

Referring i ps

Fetches IP addresses that are sources of backlinks for a specified target domain, root domain, or URL.

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.

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.

FRAMEWORKS

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OpenClaw logo

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Hermes logo

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CLI logo

CLI

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Google ADK logo

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LangChain logo

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Vercel AI SDK logo

Vercel AI SDK

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LlamaIndex logo

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CrewAI logo

CrewAI

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OpenCode logo

OpenCode

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VS Code logo

VS Code

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FAQ

Frequently asked questions

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.

Yes, you can. Mastra AI 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.

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.

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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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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Jerome Leclanche
Co-Founder, Ingram Technologies