How to integrate Sendbird MCP with Pydantic AI

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Introduction

This guide walks you through connecting Sendbird to Pydantic AI using the Composio tool router. By the end, you'll have a working Sendbird agent that can add users to a group chat channel, ban a disruptive user from group chat, get unread message count for a user, create a new group channel with members through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Sendbird account through Composio's Sendbird 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Sendbird
  • 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 Sendbird 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 Sendbird MCP server, and what's possible with it?

The Sendbird MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Sendbird account. It provides structured and secure access to your in-app chat, voice, and video features, so your agent can perform actions like creating group channels, managing users, moderating conversations, and tracking unread message counts on your behalf.

  • Group channel management: Let your agent create new group channels, add or ban members, and delete channels as needed to keep conversations organized and secure.
  • User account administration: Automatically register new users or remove users from your Sendbird application, simplifying user lifecycle management.
  • Message moderation and cleanup: Empower your agent to delete specific messages—helping enforce community guidelines and remove unwanted content instantly.
  • Unread count and status tracking: Retrieve up-to-date counts of unread messages, mentions, and channel invitations for any user to surface important conversations.
  • Channel preference insights: Access and update user count preferences in group channels, tailoring notification and message delivery based on user needs.

Supported Tools & Triggers

Tools
Add Members To Group ChannelTool to add members to a group channel.
Ban User from Group ChannelTool to ban a user from a group channel.
Create Group ChannelTool to create a new group channel.
Create Sendbird UserTool to create a new user.
Delete Group ChannelTool to delete a specific group channel.
Delete MessageTool to delete a specific message in a sendbird group channel.
Delete Sendbird UserTool to delete a sendbird user.
Get Count Preference Of ChannelTool to retrieve a user's count preference for a specific group channel.
Sendbird Get Group Channel Count by Join StatusTool to retrieve number of group channels by join status for a user.
Sendbird Get Unread Item CountTool to retrieve a user's unread item counts.
Issue Session TokenTool to issue a session token for a user.
Leave Group ChannelsTool to leave group channels for a user.
List Banned MembersTool to list banned members in a group channel.
List Group ChannelsTool to list group channels.
List Group Channel MembersTool to list members of a group channel.
List Operators by Custom Channel TypeTool to list operators of a channel by custom channel type.
List Group Channel OperatorsTool to list operators of a group channel.
List Open Channel OperatorsTool to list operators of an open channel.
List UsersTool to retrieve a list of users.
Mark All User Messages As ReadTool to mark all of a user's messages as read in group channels.
Mute UserTool to mute a user in a group channel.
Register Operators by Custom Channel TypeTool to register users as operators to channels by custom channel type.
Register Group Channel OperatorsTool to register one or more users as operators in a sendbird group channel.
Register Operators to Open ChannelTool to register operators to an open channel.
Revoke All Session TokensTool to revoke all session tokens for a user.
Sendbird View MessageTool to view a specific message in a group channel.
Sendbird View UserTool to view user information.
Send MessageTool to send a message to a group channel.
Unban User from Group ChannelTool to unban a user from a group channel.
Unmute UserTool to unmute a user in a group channel.
Unregister Operators Custom Channel TypeTool to unregister operators from channels by custom channel type.
Update Count Preference Of ChannelTool to update a user's unread count preference for a specific group channel.
Update Group ChannelTool to update group channel information.
Sendbird Update MessageTool to update an existing group channel message in sendbird.
Update Sendbird UserTool to update a user's information.
Sendbird View Group ChannelTool to view information about a specific group channel.
View UserTool to retrieve information about a specific sendbird user.

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, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active 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

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

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

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

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 Sendbird
  • MCPServerStreamableHTTP connects to the Sendbird MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

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 Sendbird
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["sendbird"],
    )
    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 Sendbird 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

Initialize the Pydantic AI Agent

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

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 Sendbird.\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
  • Sendbird API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

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 Sendbird and Pydantic AI:

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 Sendbird
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["sendbird"],
    )
    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
    sendbird_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[sendbird_mcp],
        instructions=(
            "You are a Sendbird assistant. Use Sendbird 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 Sendbird.\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 Sendbird through Composio's Tool Router. With this setup, your agent can perform real Sendbird 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 + Sendbird for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

How to build Sendbird MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Sendbird MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Sendbird MCP with Claude Agent SDK

Google ADK

Google ADK

Use Sendbird MCP with Google ADK

LangChain

LangChain

Use Sendbird MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Sendbird MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Sendbird MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Sendbird MCP with LlamaIndex

CrewAI

CrewAI

Use Sendbird MCP with CrewAI

FAQ

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

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

Can I use Tool Router MCP with Pydantic AI?

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 Sendbird tools.

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

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

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