How to integrate Keyword MCP with Pydantic AI

This guide walks you through connecting Keyword to Pydantic AI 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 Pydantic AI 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 Pydantic AI 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 Pydantic AI 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Keyword
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Keyword workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Keyword
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Keyword
  • MCPServerStreamableHTTP connects to the Keyword MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Keyword
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["keyword"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Keyword 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
keyword_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[keyword_mcp],
    instructions=(
        "You are a Keyword assistant. Use Keyword tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Keyword endpoint
  • The agent uses GPT-5 to interpret user commands and perform Keyword operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Keyword.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Keyword API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Keyword
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["keyword"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    keyword_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[keyword_mcp],
        instructions=(
            "You are a Keyword assistant. Use Keyword tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Keyword.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

Conclusion

You've built a Pydantic AI agent that can interact with Keyword through Composio's Tool Router. With this setup, your agent can perform real Keyword actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Keyword for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
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. Pydantic 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 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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