# How to integrate Dailybot MCP with Pydantic AI

```json
{
  "title": "How to integrate Dailybot MCP with Pydantic AI",
  "toolkit": "Dailybot",
  "toolkit_slug": "dailybot",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/dailybot/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/dailybot/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:08:15.632Z"
}
```

## Introduction

This guide walks you through connecting Dailybot to Pydantic AI using the Composio tool router. By the end, you'll have a working Dailybot agent that can send a standup reminder to your team, give kudos to top performers this week, list all active dailybot workflows through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Dailybot account through Composio's Dailybot MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Dailybot with

- [OpenAI Agents SDK](https://composio.dev/toolkits/dailybot/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/dailybot/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/dailybot/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/dailybot/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/dailybot/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/dailybot/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/dailybot/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/dailybot/framework/cli)
- [Google ADK](https://composio.dev/toolkits/dailybot/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/dailybot/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/dailybot/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/dailybot/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/dailybot/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/dailybot/framework/crew-ai)

## 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 Dailybot
- 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 Dailybot 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 Dailybot MCP server, and what's possible with it?

The Dailybot MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dailybot account. It provides structured and secure access to your team’s Dailybot workspace, so your agent can perform actions like sending messages, running workflows, managing users, and automating recognition on your behalf.
- Automated team messaging and notifications: Let your agent instantly send updates, reminders, or announcements to specific users or channels via Dailybot, complete with markdown formatting.
- Workflow discovery and automation: Effortlessly find, list, or retrieve details about team workflows, enabling your agent to help coordinate or trigger automated routines across your organization.
- User management and lookup: Quickly fetch information about any user in your Dailybot workspace, including status, profile details, and organizational context, for personalized communication and reporting.
- Kudos and team recognition: Enable your agent to give kudos to one or multiple teammates, supporting a culture of appreciation and motivation directly from your chat platforms.
- Comprehensive organization insights: Retrieve and analyze lists of all users or workflows, helping your agent surface insights, generate reports, or keep your team directory up to date automatically.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DAILYBOT_CREATE_CHECKIN` | Create Check-in | Tool to create a check-in based on a template in DailyBot. Use when you need to set up a new recurring check-in (like daily standups, weekly syncs) for a team. The check-in can be scheduled with custom triggers, reminders, and reporting channels. |
| `DAILYBOT_FIND_USER` | Find User by UUID | This tool allows you to find and retrieve information about a specific user in DailyBot. It uses the provided user_uuid to lookup the user and returns detailed information including the user's uuid, full name, image, username, occupation, birth date, chat platform data, and organization details. |
| `DAILYBOT_FIND_WORKFLOW` | Find Workflow by Name | Fetches one page of workflows from DailyBot, optionally filtered by name. DailyBot exposes HATEOAS pagination on `/v1/workflows/`: each response carries a `next` field that is the full URL of the next page. ONE DailyBot API call is made per invocation; pagination is caller-driven via the `cursor` parameter (pass the previous response's `next_cursor`) and the `next_cursor` / `has_next_page` fields in the response. When `workflow_name` is supplied, the current page is filtered locally (case-insensitive) and only the matching workflow is returned; if the name is not found on this page, callers should re-invoke with `cursor=next_cursor` to continue searching. |
| `DAILYBOT_GET_USERS` | Get All Users | Retrieves a paginated list of all users within the authenticated organization from DailyBot. This action requires no input parameters and returns comprehensive user information including: - User identification (UUID, full name, username) - Status information (is_active, bot_enabled) - Work details (role, timezone, occupation, work_days, work hours) - Time off information (timeoff_start, timeoff_end) - Chat platform integration data (user_external_id, external_grid_id) - Organization details The response includes pagination fields (count, next, previous) for navigating large user lists. All users in the organization are returned regardless of their active status or role. |
| `DAILYBOT_GIVE_KUDOS` | Give Kudos to Users | This tool allows giving kudos to one or multiple users in DailyBot. Kudos can be given either on behalf of DailyBot or the API key owner. |
| `DAILYBOT_SEND_MESSAGE` | Send Message | This tool allows sending a message through DailyBot to either specific users or channels/rooms. The message can include markdown formatting. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Dailybot MCP server is an implementation of the Model Context Protocol that connects your AI agent to Dailybot. It provides structured and secure access so your agent can perform Dailybot operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 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

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install the required libraries.
What's happening:
- composio connects your agent to external SaaS tools like Dailybot
- pydantic-ai lets you create structured AI agents with tool support
- python-dotenv loads your environment variables securely from a .env file
```bash
pip install composio pydantic-ai python-dotenv
```

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key
```

### 4. Import dependencies

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

### 5. Create a Tool Router Session

What's happening:
- We're creating a Tool Router session that gives your agent access to Dailybot 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
```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 Dailybot
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["dailybot"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
```

### 6. Initialize the Pydantic AI Agent

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

### 7. Build the chat interface

What's happening:
- The agent reads input from the terminal and streams its response
- Dailybot API calls happen automatically under the hood
- The model keeps conversation history to maintain context across turns
```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 Dailybot.\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()
```

### 8. Run the application

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

## Complete Code

```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 Dailybot
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["dailybot"],
    )
    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
    dailybot_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[dailybot_mcp],
        instructions=(
            "You are a Dailybot assistant. Use Dailybot 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 Dailybot.\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 Dailybot through Composio's Tool Router. With this setup, your agent can perform real Dailybot 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 + Dailybot 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 Dailybot MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/dailybot/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/dailybot/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/dailybot/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/dailybot/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/dailybot/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/dailybot/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/dailybot/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/dailybot/framework/cli)
- [Google ADK](https://composio.dev/toolkits/dailybot/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/dailybot/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/dailybot/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/dailybot/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/dailybot/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/dailybot/framework/crew-ai)

## Related Toolkits

- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Slack](https://composio.dev/toolkits/slack) - Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.
- [Gong](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.
- [Microsoft teams](https://composio.dev/toolkits/microsoft_teams) - Microsoft Teams is a collaboration platform that combines chat, meetings, and file sharing within Microsoft 365. It keeps distributed teams connected and productive through seamless virtual communication.
- [Slackbot](https://composio.dev/toolkits/slackbot) - Slackbot is a conversational automation tool for Slack that handles reminders, notifications, and automated responses. It boosts team productivity by streamlining onboarding, answering FAQs, and managing timely alerts—all right inside Slack.
- [2chat](https://composio.dev/toolkits/_2chat) - 2chat is an API platform for WhatsApp and multichannel text messaging. It streamlines chat automation, group management, and real-time messaging for developers.
- [Agent mail](https://composio.dev/toolkits/agent_mail) - Agent mail provides AI agents with dedicated email inboxes for sending, receiving, and managing emails. It empowers agents to communicate autonomously with people, services, and other agents—no human intervention needed.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Chatwork](https://composio.dev/toolkits/chatwork) - Chatwork is a team communication platform with group chats, file sharing, and task management. It helps businesses boost collaboration and streamline productivity.
- [Clickmeeting](https://composio.dev/toolkits/clickmeeting) - ClickMeeting is a cloud-based platform for running online meetings and webinars. It helps businesses and individuals host, manage, and engage virtual audiences with ease.
- [Confluence](https://composio.dev/toolkits/confluence) - Confluence is Atlassian's team collaboration and knowledge management platform. It helps your team organize, share, and update documents and project content in one secure workspace.
- [Dialmycalls](https://composio.dev/toolkits/dialmycalls) - Dialmycalls is a mass notification service for sending voice and text messages to contacts. It helps teams and organizations quickly broadcast urgent alerts and updates.
- [Dialpad](https://composio.dev/toolkits/dialpad) - Dialpad is a cloud-based business phone and contact center system for teams. It unifies voice, video, messaging, and meetings across your devices.
- [Discord](https://composio.dev/toolkits/discord) - Discord is a real-time messaging and VoIP platform for communities and teams. It lets users chat, share media, and collaborate across public and private channels.
- [Discordbot](https://composio.dev/toolkits/discordbot) - Discordbot is an automation tool for Discord servers that handles moderation, messaging, and user engagement. It helps communities run smoothly by automating routine and complex tasks.
- [Echtpost](https://composio.dev/toolkits/echtpost) - Echtpost is a secure digital communication platform for encrypted document and message exchange. It ensures confidential data stays private and protected during transmission.
- [Egnyte](https://composio.dev/toolkits/egnyte) - Egnyte is a cloud-based platform for secure file sharing, storage, and governance. It helps teams collaborate efficiently while maintaining data compliance and security.
- [Google Meet](https://composio.dev/toolkits/googlemeet) - Google Meet is a secure video conferencing platform for virtual meetings, chat, and screen sharing. It helps teams connect, collaborate, and communicate seamlessly from anywhere.
- [Heartbeat](https://composio.dev/toolkits/heartbeat) - Heartbeat is a plug-and-play platform for building and managing online communities. It helps you organize users, channels, events, and discussions in one place.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Dailybot MCP?

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

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

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

---
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