How to integrate Semrush MCP with LangChain

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Introduction

This guide walks you through connecting Semrush to LangChain 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', list ad copies seen for my competitor through natural language commands.

This guide will help you understand how to give your LangChain 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.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Semrush project to Composio
  • Create a Tool Router MCP session for Semrush
  • Initialize an MCP client and retrieve Semrush tools
  • Build a LangChain agent that can interact with Semrush
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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 & Triggers

Tools
Get ad copiesRetrieves 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 textsUse 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 profileRetrieves 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 backlinksFetches 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.
Backlinks overviewProvides a csv-formatted summary of backlinks, including authority score and link type breakdowns, for a specified and publicly accessible domain, root domain, or url.
Batch comparisonCompares backlink profiles for multiple specified targets (domains, subdomains, or urls) to analyze and compare link-building efforts.
Batch keyword overviewFetches 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 keywordFetches broad match keywords for a given phrase; `display sort` and `display filter` parameters are defined but currently not utilized by the api call.
Get categoriesRetrieves categories and their 0-1 confidence ratings for a specified domain, subdomain, or url, with results sorted by rating.
Get categories profileRetrieves 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 dataRetrieves 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.
Get competitors in organic searchUse 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 searchRetrieves a list of a domain's competitors in paid search results from a specified regional database.
Get domain ad historyRetrieves 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 pagesFetches 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 keywordsRetrieves 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 subdomainsRetrieves 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 keywordsFetches keywords driving paid search traffic to a specified, existing domain using a supported semrush regional database.
Get PLA search keywords for a domainRetrieves product listing ad (pla) search keywords for a specified domain from a semrush regional database.
Compare domainsAnalyzes 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 dataRetrieves monthly historical backlink and referring domain data for a specified root domain, returned as a time series string with newest records first.
Get indexed pagesRetrieves 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 difficultyDetermines 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 databasesFetches a keyword overview from semrush for a specified phrase, including metrics like search volume, cpc, and competition.
Get keyword overview for one databaseFetches a keyword summary for a specified phrase from a chosen regional database.
Get keywords ads historyFetches 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 resultsRetrieves 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 resultsFetches domains ranking in google's paid search results (adwords) for a specified keyword and regional database.
Phrase questionsFetches 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 competitorsRetrieves domains competing with a specified domain in google's product listing ads (pla) from a given semrush regional database.
Get PLA copiesFetches product listing ad (pla) copies that semrush observed for a domain in google's paid search results.
Get referring domainsRetrieves a report as a text string (e.
Get referring domains by countryGenerates a csv report detailing the geographic distribution of referring domains (by country, determined via ip address) for a specified, publicly accessible target.
Referring i psFetches ip addresses that are sources of backlinks for a specified target domain, root domain, or url.
Find related keywordsCall 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 distributionFetches a report on the top-level domain (tld) distribution of referring domains for a specified target, useful for analyzing geographic or categorical backlink diversity.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Semrush functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Semrush tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Semrush
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['semrush']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Semrush tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Semrush tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "semrush-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Semrush MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Semrush tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Semrush related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

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

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['semrush']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "semrush-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Semrush related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Semrush through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

How to build Semrush MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Semrush MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Semrush MCP with Claude Agent SDK

Google ADK

Google ADK

Use Semrush MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Semrush MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Semrush MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Semrush MCP with LlamaIndex

CrewAI

CrewAI

Use Semrush MCP with CrewAI

FAQ

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 LangChain?

Yes, you can. LangChain 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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