How to integrate Ably MCP with Pydantic AI

This guide walks you through connecting Ably to Pydantic AI using the Composio tool router. By the end, you'll have a working Ably agent that can list all active channels and their details, get message history from 'support-chat' channel, show presence history for 'live-event' channel through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Ably account through Composio's Ably MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.

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Introduction

This guide walks you through connecting Ably to Pydantic AI using the Composio tool router. By the end, you'll have a working Ably agent that can list all active channels and their details, get message history from 'support-chat' channel, show presence history for 'live-event' channel through natural language commands.

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

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

Also integrate Ably with

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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 Ably
  • 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 Ably 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 Ably MCP server, and what's possible with it?

The Ably MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ably account. It provides structured and secure access to your real-time messaging infrastructure, so your agent can manage channels, monitor presence, analyze usage, and handle messaging workflows for your applications.

  • Channel management and creation: Seamlessly create, initialize, or retrieve real-time messaging channels so your agent can orchestrate chat, data sync, and collaboration features on demand.
  • Presence tracking and analytics: Ask your agent to query current presence states or review historical presence data across multiple channels, gaining insights into user activity and engagement patterns.
  • Message history and audit: Retrieve detailed message histories from any channel, enabling your agent to audit communication, recover missed messages, or analyze message flows for debugging and compliance.
  • Push notification subscription management: Let your agent list, manage, or unsubscribe devices from push notification channels, ensuring targeted and controlled delivery of real-time alerts to clients.
  • Application statistics and monitoring: Have your agent fetch in-depth usage metrics—like message counts, channel activity, and API request stats—so you can monitor health, optimize performance, and manage resources with confidence.

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 Ably
  • 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 Ably
  • MCPServerStreamableHTTP connects to the Ably 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 Ably
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["ably"],
    )
    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 Ably 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
ably_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[ably_mcp],
    instructions=(
        "You are a Ably assistant. Use Ably tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Ably endpoint
  • The agent uses GPT-5 to interpret user commands and perform Ably 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 Ably.\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
  • Ably 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 Ably 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 Ably
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["ably"],
    )
    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
    ably_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[ably_mcp],
        instructions=(
            "You are a Ably assistant. Use Ably 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 Ably.\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 Ably through Composio's Tool Router. With this setup, your agent can perform real Ably 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 + Ably 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 Ably action and event your agent gets out of the box.

Query Batch Presence

This tool enables querying the presence states of multiple channels in a single API request.

Query Batch Presence History

This tool enables querying presence history for multiple channels in a single API request.

Delete Channel Subscription

This tool allows you to unsubscribe devices or clients from push notifications for specific channels.

Get Channel Details

This tool retrieves metadata and details for a specific channel in Ably.

Get Channel History

This tool retrieves the message history for a specified Ably channel.

Get Channel Presence

Tool to obtain the set of members currently present for a channel.

Get Message Versions

Tool to retrieve all historical versions of a specific message from an Ably channel.

Get Channel Presence History

This tool retrieves the history of presence messages for a specified channel in Ably.

Get Push Device Registration

Tool to get the full details of a device registration for push notifications.

Get Ably Service Time

This tool retrieves the current server time from Ably's service in milliseconds since the epoch.

Get Application Stats

This tool retrieves your application's usage statistics from Ably.

List Channels

Tool to enumerate all active channels in the Ably application.

List Push Channels

Tool to list all channels with at least one subscribed device.

List Push Channel Subscriptions

This tool retrieves a list of all push notification channel subscriptions.

List Registered Push Devices

Tool to list all devices registered for receiving push notifications in your Ably application.

Patch Push Device Registration

Tool to partially update specific attributes of an existing device registration in Ably's push notification system.

Batch Publish Messages

Tool to batch publish messages to multiple channels in parallel.

Publish Message to Channel

This tool will allow users to publish a message to a specified Ably channel using a POST request.

Publish Push Notification

Tool to publish a push notification directly to device(s) via Ably's Push Notifications API.

Batch Publish Push Notifications

Tool to batch publish push notifications directly to specific recipients.

Register Push Device

Tool to register a device for receiving push notifications in Ably.

Request Access Token

Request an access token for Ably authentication.

Unregister All Push Devices

Tool to unregister matching devices for push notifications.

Unregister Push Device

Tool to unregister a single device from push notifications in Ably.

Update Push Device Registration

Tool to update (upsert) a device registration for push notifications in Ably.

FRAMEWORKS

How to build Ably MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Ably MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Ably MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Ably MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Ably MCP with Claude Cowork

Codex logo

Codex

Use Ably MCP with Codex

OpenClaw logo

OpenClaw

Use Ably MCP with OpenClaw

Hermes logo

Hermes

Use Ably MCP with Hermes

CLI logo

CLI

Use Ably MCP with CLI

Google ADK logo

Google ADK

Use Ably MCP with Google ADK

LangChain logo

LangChain

Use Ably MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Ably MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Ably MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Ably MCP with LlamaIndex

CrewAI logo

CrewAI

Use Ably MCP with CrewAI

FAQ

Frequently asked questions

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

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

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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.

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