# How to integrate Vestaboard MCP with Autogen ```json { "title": "How to integrate Vestaboard MCP with Autogen", "toolkit": "Vestaboard", "toolkit_slug": "vestaboard", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/vestaboard/framework/autogen", "markdown_url": "https://composio.dev/toolkits/vestaboard/framework/autogen.md", "updated_at": "2026-05-06T08:33:13.117Z" } ``` ## Introduction This guide walks you through connecting Vestaboard to AutoGen using the Composio tool router. By the end, you'll have a working Vestaboard agent that can list all your vestaboard subscriptions, send 'lunch is ready!' to kitchen board, display daily quote on office vestaboard through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Vestaboard account through Composio's Vestaboard MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Vestaboard with - [OpenAI Agents SDK](https://composio.dev/toolkits/vestaboard/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/vestaboard/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/vestaboard/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/vestaboard/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/vestaboard/framework/codex) - [OpenClaw](https://composio.dev/toolkits/vestaboard/framework/openclaw) - [Hermes](https://composio.dev/toolkits/vestaboard/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/vestaboard/framework/cli) - [Google ADK](https://composio.dev/toolkits/vestaboard/framework/google-adk) - [LangChain](https://composio.dev/toolkits/vestaboard/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/vestaboard/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/vestaboard/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/vestaboard/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/vestaboard/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 Vestaboard - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Vestaboard tools - Run a live chat loop where you ask the agent to perform Vestaboard 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 Vestaboard MCP server, and what's possible with it? The Vestaboard MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Vestaboard account. It provides structured and secure access to your Vestaboard displays, so your agent can perform actions like listing subscriptions, sending custom messages, and managing display content on your behalf. - List all Vestaboard subscriptions: Easily retrieve and review every Vestaboard subscription linked to your account so you know exactly which displays your agent can manage. - Send messages to any board: Direct your agent to post custom messages or notifications to a specific Vestaboard subscription in real time, perfect for reminders, daily schedules, or inspirational quotes. - Automate display updates: Schedule or trigger automatic content updates across multiple Vestaboards without manual effort, keeping your displays fresh and relevant. - Centralized display management: Manage all your connected Vestaboards from one place—no need to hop between apps or devices to update your displays. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `VESTABOARD_LIST_SUBSCRIPTIONS` | List Subscriptions | Tool to list all subscriptions accessible to the authenticated user. use when you need to retrieve your subscriptions. example: "list my subscriptions on vestaboard." | | `VESTABOARD_SUBSCRIPTION_API_SEND_MESSAGE` | Send Message to Subscription | Tool to send a message to a specific vestaboard subscription. use after confirming you have the subscription id. example: "send 'hello!' to subscription sub ab12cd34ef." | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Vestaboard MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Vestaboard. Instead of manually wiring Vestaboard 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 Vestaboard 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 Vestaboard 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 Vestaboard 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 Vestaboard 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 Vestaboard session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["vestaboard"] ) 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 Vestaboard 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 Vestaboard assistant agent with MCP tools agent = AssistantAgent( name="vestaboard_assistant", description="An AI assistant that helps with Vestaboard 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 Vestaboard 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 Vestaboard 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 Vestaboard session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["vestaboard"] ) 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 Vestaboard assistant agent with MCP tools agent = AssistantAgent( name="vestaboard_assistant", description="An AI assistant that helps with Vestaboard 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 Vestaboard 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 Vestaboard 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 Vestaboard, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Vestaboard MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/vestaboard/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/vestaboard/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/vestaboard/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/vestaboard/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/vestaboard/framework/codex) - [OpenClaw](https://composio.dev/toolkits/vestaboard/framework/openclaw) - [Hermes](https://composio.dev/toolkits/vestaboard/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/vestaboard/framework/cli) - [Google ADK](https://composio.dev/toolkits/vestaboard/framework/google-adk) - [LangChain](https://composio.dev/toolkits/vestaboard/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/vestaboard/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/vestaboard/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/vestaboard/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/vestaboard/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. - [Dailybot](https://composio.dev/toolkits/dailybot) - DailyBot streamlines team collaboration with chat-based standups, reminders, and polls. It keeps work flowing smoothly in your favorite messaging platforms. - [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. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Vestaboard MCP? With a standalone Vestaboard MCP server, the agents and LLMs can only access a fixed set of Vestaboard tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Vestaboard 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 Vestaboard tools. ### Can I manage the permissions and scopes for Vestaboard while using Tool Router? Yes, absolutely. You can configure which Vestaboard 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 Vestaboard data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)