How to integrate Keyword MCP with Autogen

This guide walks you through connecting Keyword to AutoGen using the Composio tool router. By the end, you'll have a working Keyword agent that can track keyword rankings for target domains, compare seo visibility across competitors, find ranking drops for tracked keywords through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Keyword account through Composio's Keyword MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Keyword.com is a digital marketing platform for search rank tracking and SEO analytics. Use it to monitor keyword performance, spot ranking changes, and measure SEO visibility.

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Introduction

This guide walks you through connecting Keyword to AutoGen using the Composio tool router. By the end, you'll have a working Keyword agent that can track keyword rankings for target domains, compare seo visibility across competitors, find ranking drops for tracked keywords through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Keyword account through Composio's Keyword MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Keyword with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Keyword
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Keyword tools
  • Run a live chat loop where you ask the agent to perform Keyword operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Keyword MCP server, and what's possible with it?

The Keyword MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Keyword account. It provides structured and secure access to your SEO projects, keywords, rankings, and performance data, so your agent can monitor search rankings, analyze keyword movement, review top pages, track share of voice, and manage keyword settings on your behalf.

  • Keyword ranking analysis: Have your agent retrieve tracked keywords, review their current ranking metrics, and examine up to 180 days of Google ranking history.
  • Project performance monitoring: Let the agent summarize active projects, inspect project details, and analyze keyword movement across projects, groups, or tags.
  • Share of voice and page insights: Direct your agent to track share of voice over time and identify top ranking pages by keyword count, average rank, search volume, and cost per click.
  • Alerts and regional tracking: Instruct your agent to review account alerts and list the Google regions tracked for each project.
  • Keyword and project management: Have your agent update keyword settings, refresh rankings on demand, or delete keywords and projects you no longer need.

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Keyword account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

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.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Keyword via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Keyword connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Keyword session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["keyword"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Keyword tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Keyword assistant agent with MCP tools
    agent = AssistantAgent(
        name="keyword_assistant",
        description="An AI assistant that helps with Keyword operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Keyword tools from the workbench
8

Run the interactive chat loop

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

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Keyword tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Keyword and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Keyword session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["keyword"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Keyword assistant agent with MCP tools
        agent = AssistantAgent(
            name="keyword_assistant",
            description="An AI assistant that helps with Keyword operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

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

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Keyword through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Keyword, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Add Keywords

Tool to add keywords to a Keyword.

Archive Project

Tool to archive a project in Keyword.

Create Project or Group

Tool to create a new project or group in Keyword.

Delete Keyword

Tool to delete a single keyword from a project or group.

Bulk delete keywords

Tool to bulk delete multiple keywords from a single project by providing keyword IDs.

Delete Project

Tool to delete a single project or group from Keyword.

Get Current User

Tool to retrieve the current authenticated user's account information.

Get Keyword

Tool to retrieve all keyword settings and ranking metrics for a single keyword.

Get Project Details

Tool to retrieve a single project's summary from Keyword.

Get Project Metrics

Retrieve keyword movement metrics for a project, group, or tag.

Get Keyword Ranking History

Tool to retrieve Google ranking history for specified keywords for up to 180 days.

Get Share of Voice History

Retrieve Share of Voice data over time for a specific project.

Get Top Pages

Tool to retrieve Top Pages data for a project showing ranking URLs with keyword counts, average rank, search volume, and cost per click metrics.

List Active Projects

Tool to retrieve all active projects with their groups, tags, and keyword counts.

List Alerts

Tool to retrieve all alerts for the Keyword.

List Keywords

Tool to retrieve all keywords and their ranking data in a project or group.

List Project Regions

Tool to list all Google regions being tracked in a Keyword.

Refresh Keywords

Tool to trigger an on-demand update for all keywords in one or more projects or groups.

Restore Archived Project

Tool to restore an archived project or group.

Update Keywords

Tool to update keyword settings in a project.

FRAMEWORKS

How to build Keyword MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Keyword MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Keyword MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Keyword MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Keyword MCP with Claude Cowork

Codex logo

Codex

Use Keyword MCP with Codex

OpenClaw logo

OpenClaw

Use Keyword MCP with OpenClaw

Hermes logo

Hermes

Use Keyword MCP with Hermes

CLI logo

CLI

Use Keyword MCP with CLI

Google ADK logo

Google ADK

Use Keyword MCP with Google ADK

LangChain logo

LangChain

Use Keyword MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Keyword MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Keyword MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Keyword MCP with LlamaIndex

CrewAI logo

CrewAI

Use Keyword MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Keyword MCP server, the agents and LLMs can only access a fixed set of Keyword tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Keyword and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Autogen 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 Keyword tools.

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

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