How to integrate Ahrefs MCP with LlamaIndex

BOOK A CALLGET STARTED FOR FREE
Framework Integration Gradient
Ahrefs Logo
LlamaIndex Logo
divider

Introduction

This guide walks you through connecting Ahrefs to LlamaIndex using the Composio tool router. By the end, you'll have a working Ahrefs agent that can get domain rating trend for competitor site, list all broken backlinks for my website, find keyword volume for 'ai tools' in us, show top referring domains for example.com through natural language commands.

This guide will help you understand how to give your LlamaIndex agent real control over a Ahrefs account through Composio's Ahrefs 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:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Ahrefs
  • Connect LlamaIndex to the Ahrefs MCP server
  • Build a Ahrefs-powered agent using LlamaIndex
  • Interact with Ahrefs 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 Ahrefs MCP server, and what's possible with it?

The Ahrefs MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ahrefs account. It provides structured and secure access to your SEO and marketing data, so your agent can perform actions like analyzing backlinks, researching keywords, auditing domain authority, and uncovering competitive insights on your behalf.

  • Comprehensive backlink analysis: Instantly retrieve detailed backlink profiles, stats, and broken link data for any website to inform your SEO strategy or spot link-building opportunities.
  • Keyword research and trends: Explore keyword overviews, search volumes by country, and discover matching or related terms to optimize content and target the right audience.
  • Domain authority tracking: Fetch up-to-date domain ratings or track historical changes to monitor the SEO health and growth of your own sites or competitors over time.
  • Batch competitor and site analysis: Analyze up to 100 domains or URLs at once to compare SEO metrics, spot weaknesses, and benchmark your performance against competitors efficiently.
  • Outbound link and partnership insights: Identify all external domains a site links to, helping you understand content strategy, partnerships, and potential link-building prospects.

Supported Tools & Triggers

Tools
Backlinks stats retrievalRetrieves comprehensive backlink statistics for a specified website or url using ahrefs' site explorer tool.
Batch Url AnalysisPerforms a batch analysis on multiple urls or domains using ahrefs' powerful seo metrics.
Domain rating for site explorerRetrieves the domain rating (dr) for a specified domain.
Domain rating historyRetrieves the historical domain rating (dr) data for a specified domain over time.
Explore keywords overviewRetrieves a comprehensive overview of keyword data from ahrefs' keywords explorer tool.
Explore keyword volume by countryRetrieves the search volume data for specified keywords across different countries using ahrefs' keywords explorer tool.
Explore linked domains of a siteRetrieves a list of external domains that the specified target website or url links to, using ahrefs' site explorer functionality.
Explore matching terms for keywordsThe keywords explorer matching terms endpoint retrieves a list of keyword phrases that match or contain the specified keyword from ahrefs' vast database.
Fetch all backlinksRetrieves a comprehensive list of backlinks for a specified website or url using ahrefs' site explorer tool.
Fetch broken backlinks dataRetrieves a list of broken backlinks for a specified website using ahrefs' site explorer tool.
Fetch competitors overviewRetrieves a comprehensive overview of competitor data in relation to keyword rankings and organic search performance.
Fetch rank tracker overviewThe getranktrackeroverview endpoint retrieves a comprehensive summary of keyword rankings and seo performance data from ahrefs' rank tracker tool.
Fetch site explorer referring domainsRetrieves a list of domains that have backlinks pointing to a specified target website.
Fetch total search volume historyRetrieves the historical total search volume data for specified keywords using ahrefs' site explorer tool.
Get serp overviewRetrieves a comprehensive overview of search engine results pages (serp) data for specified keywords or queries.
Get site audit projectsRetrieves a list of site audit projects associated with the authenticated ahrefs account.
Get site explorer country metricsRetrieves country-specific site explorer metrics for a given website from ahrefs.
Get site explorer linked anchors externalThe site-explorer-linked-anchors-external endpoint retrieves data about external anchor texts linking to a specified target website.
Get url rating historyRetrieves the historical url rating data for a specified url over time.
Linked anchors explorerRetrieves information about internal linked anchors for a specified website using the ahrefs api.
List best by external linksThe 'get best by external links' endpoint retrieves a list of pages from a specified website, ranked by the number of external links pointing to them.
Pages by traffic overviewRetrieves a list of pages from a specified website, ordered by their estimated organic search traffic.
Retrieve anchor dataRetrieves anchor text data for a specified website or url using ahrefs' site explorer tool.
Retrieve best by internal linksRetrieves data on the best-performing internal links within a specified website using ahrefs' site explorer feature.
Retrieve crawler ip rangesRetrieves the list of ip address ranges used by ahrefs' web crawler (ahrefsbot).
Retrieve organic competitorsThe getorganiccompetitors endpoint in the ahrefs api provides a comprehensive analysis of websites competing for organic search rankings with a specified target domain.
Retrieve organic keywordsRetrieves organic keywords data for a specified website using ahrefs' site explorer tool.
Retrieve outlinks statsRetrieves comprehensive statistics about outgoing links (outlinks) from a specified website using ahrefs' site explorer tool.
Retrieve paid pages dataRetrieves information about paid pages (ppc advertising) for a specified website using ahrefs' site explorer tool.
Retrieve public crawler ipsRetrieves a list of ip addresses currently used by ahrefsbot, ahrefs' web crawler.
Retrieve related termsThe keywords explorer related terms endpoint retrieves a list of related terms for a given keyword using ahrefs' extensive keyword database.
Retrieve site explorer keywords historyRetrieves historical keyword performance data for a specified website or domain using ahrefs' site explorer.
Retrieve site explorer metricsThe getsiteexplorermetrics endpoint retrieves comprehensive seo metrics for a specified website using ahrefs' site explorer tool.
Retrieve site explorer metrics historyRetrieves historical seo metrics data for a specified website over a given time period.
Retrieve site explorer pages historyThe get site explorer pages history endpoint retrieves historical data about specific pages or domains from ahrefs' site explorer.
Retrieve site explorer referring domains historyRetrieves the historical data of referring domains for a specified website or url over time.
Retrieve subscription limits and usageRetrieves detailed information about the current subscription limits and usage for an ahrefs account.
Retrieve top pages from site explorerRetrieves data about the top-performing pages of a specified website using ahrefs' site explorer tool.
Retrieve volume historyRetrieves the historical search volume data for a specified keyword using ahrefs' keywords explorer tool.
Search suggestions explorerRetrieves search suggestions for a given keyword or phrase using ahrefs' keywords explorer tool.

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 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 Ahrefs account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Ahrefs

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

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 Ahrefs access

Import modules

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()

Create a new file called ahrefs_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

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")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

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=["ahrefs"],
    )

    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 Ahrefs actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Ahrefs actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

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, ahrefs)
  • 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 Ahrefs tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

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}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Ahrefs database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

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!")

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 Ahrefs

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Ahrefs, then start asking questions.

Complete Code

Here's the complete code to get you started with Ahrefs and LlamaIndex:

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=["ahrefs"],
    )

    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 Ahrefs actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Ahrefs 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!")

Conclusion

You've successfully connected Ahrefs to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Ahrefs 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 Ahrefs MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Ahrefs MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Ahrefs MCP with Claude Agent SDK

Google ADK

Google ADK

Use Ahrefs MCP with Google ADK

LangChain

LangChain

Use Ahrefs MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Ahrefs MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Ahrefs MCP with Mastra AI

CrewAI

CrewAI

Use Ahrefs MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Ahrefs MCP?

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

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

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

Used by agents from

Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Book a call↗Get started for free