# How to integrate Dailybot MCP with Autogen

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

## Introduction

This guide walks you through connecting Dailybot to AutoGen 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 AutoGen 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:
- 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 Dailybot
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Dailybot tools
- Run a live chat loop where you ask the agent to perform Dailybot 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 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 agents and assistants directly to Dailybot. Instead of manually wiring Dailybot APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Dailybot account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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 Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Dailybot via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

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 Dailybot connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Dailybot tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```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 Dailybot session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["dailybot"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

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
```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")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Dailybot tools from the workbench
```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 Dailybot assistant agent with MCP tools
    agent = AssistantAgent(
        name="dailybot_assistant",
        description="An AI assistant that helps with Dailybot operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Dailybot 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
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Dailybot 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")
```

## Complete Code

```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 Dailybot session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["dailybot"]
    )
    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 Dailybot assistant agent with MCP tools
        agent = AssistantAgent(
            name="dailybot_assistant",
            description="An AI assistant that helps with Dailybot 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 Dailybot 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 Dailybot 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 Dailybot, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## 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.
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- [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 Autogen?

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 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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