# How to integrate Botstar MCP with Autogen ```json { "title": "How to integrate Botstar MCP with Autogen", "toolkit": "Botstar", "toolkit_slug": "botstar", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/botstar/framework/autogen", "markdown_url": "https://composio.dev/toolkits/botstar/framework/autogen.md", "updated_at": "2026-05-12T10:03:49.150Z" } ``` ## Introduction This guide walks you through connecting Botstar to AutoGen using the Composio tool router. By the end, you'll have a working Botstar agent that can open live chat widget for new visitor, update user profile in current chat session, retrieve chatbot application id for setup through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Botstar account through Composio's Botstar MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Botstar with - [OpenAI Agents SDK](https://composio.dev/toolkits/botstar/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/botstar/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/botstar/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/botstar/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/botstar/framework/codex) - [OpenClaw](https://composio.dev/toolkits/botstar/framework/openclaw) - [Hermes](https://composio.dev/toolkits/botstar/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/botstar/framework/cli) - [Google ADK](https://composio.dev/toolkits/botstar/framework/google-adk) - [LangChain](https://composio.dev/toolkits/botstar/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/botstar/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/botstar/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/botstar/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/botstar/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 Botstar - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Botstar tools - Run a live chat loop where you ask the agent to perform Botstar 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 Botstar MCP server, and what's possible with it? The Botstar MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Botstar account. It provides structured and secure access to your chatbot operations, so your agent can perform actions like managing live chat sessions, updating user details, retrieving app parameters, and sending data between webviews and your bot—all on your behalf. - Live chat session control: Programmatically open, close, or reinitialize the Botstar live chat widget to manage user interactions in real time. - Automated user profile updates: Let your agent update user details and profile attributes during an active chatbot conversation for a more personalized experience. - Webview data exchange: Seamlessly send responses from webviews back to the chatbot or retrieve parameters passed from the bot to your webview for dynamic content handling. - Custom callback registration: Set up onOpen and onClose event handlers so your agent can trigger actions whenever users interact with the chat window. - Application ID and configuration retrieval: Fetch essential Botstar application IDs and parameters for smooth widget initialization and advanced bot customization. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `BOTSTAR_CREATE_BOT` | Create Bot | Tool to create a new bot in BotStar. Use when you need to create a new bot instance with a specific name. | | `BOTSTAR_CREATE_BOT_ATTRIBUTE` | Create Bot Attribute | Tool to create a new bot attribute in BotStar. Bot attributes are global variables for a bot and support multilingual values. Use when you need to define custom data fields for your bot. | | `BOTSTAR_CREATE_CMS_ENTITY` | Create CMS Entity | Tool to create a CMS entity in BotStar with a name and optional fields. Use when you need to define a new content structure with custom fields supporting various data types. | | `BOTSTAR_CREATE_ENTITY_FIELDS` | Create Entity Fields | Tool to create entity field(s) in BotStar CMS. Supports multiple field types including text, multiple_values, single_option, multiple_options, image, date, and entity. Use when you need to add new fields to an existing entity. | | `BOTSTAR_CREATE_ENTITY_ITEM` | Create Entity Item | Tool to create a new entity item in BotStar CMS. Use when adding items to a CMS entity with custom field values. | | `BOTSTAR_CREATE_USER_ATTRIBUTES` | Create User Attributes | Tool to create custom user attributes in BotStar. Use when you need to define new custom attributes for users with specified field name and type. | | `BOTSTAR_DELETE_BOT_ATTRIBUTE` | Delete Bot Attribute | Tool to delete a bot attribute by ID. Use when you need to remove a custom attribute from a bot. | | `BOTSTAR_DELETE_CMS_ENTITY` | Delete CMS Entity | Tool to delete a CMS entity by ID. Use when you need to remove an entity from the bot's content management system. | | `BOTSTAR_DELETE_ENTITY_FIELDS` | Delete Entity Fields | Tool to delete entity field(s) from a CMS entity. Use when you need to remove fields from a CMS entity by their unique names. | | `BOTSTAR_DELETE_ENTITY_ITEM` | Delete Entity Item | Tool to delete an entity item from a CMS entity. Use when you need to remove a specific item from a bot's CMS entity. | | `BOTSTAR_GET_BOT` | Get Bot | Tool to get your bot by bot ID. Use when you need detailed bot information including ID, name, and team name. | | `BOTSTAR_GET_BOT_APP_ID` | Get BotStar Application IDs | Tool to retrieve the BotStar application ID (`appId`). Use when initializing or reinitializing the live chat widget. | | `BOTSTAR_GET_CMS_ENTITY` | Get CMS Entity | Tool to get a specific CMS entity by ID. Returns entity details including fields configuration. Use when you need to retrieve metadata about a CMS entity structure. | | `BOTSTAR_GET_ENTITY_ITEM` | Get Entity Item | Tool to retrieve a specific item from a CMS entity with all field values. Use when you need to get detailed information about a single entity item. | | `BOTSTAR_LIST_BOT_ATTRIBUTES` | List Bot Attributes | Tool to get all bot attributes from BotStar. Returns array of bot attributes with id, name, desc, value, and data_type. Use when you need to retrieve or inspect all attributes configured for a bot. | | `BOTSTAR_LIST_BOTS` | List Bots | Tool to get your list of bots. Use when you need to retrieve all bots associated with your account. Returns an array of bots with their id, name, and team_name. | | `BOTSTAR_LIST_CMS_ENTITIES` | List CMS Entities | Tool to retrieve all CMS entities for a bot. Use when you need to access entity definitions, field configurations, or available entity schemas. | | `BOTSTAR_LIST_ENTITY_ITEMS` | List Entity Items | Tool to retrieve all entity items with pagination support. Use when you need to list CMS entity items, with optional filtering by name and status. | | `BOTSTAR_LIVECHAT_BOOT` | Livechat boot | Tool to reinitialize the live chat widget with provided data. Use after initial load to reset or update widget configuration. | | `BOTSTAR_LIVECHAT_CLOSE` | Close BotStar Livechat Widget | Tool to hide the live chat window. Use when the chat widget is configured in livechat or popup mode. | | `BOTSTAR_BOTSTAR_LIVECHAT_ON_CLOSE` | BotStar LiveChat onClose Callback | Tool to register a callback when the chat window is closed. Use after the widget is initialized. Example prompt: "Register an onClose handler that logs 'Goodbye!' to the console." | | `BOTSTAR_LIVECHAT_ON_OPEN` | Livechat on open | Tool to register a callback when the chat window is opened. Use after widget initialization. | | `BOTSTAR_LIVECHAT_OPEN` | Livechat open | Tool to show the live chat window. Use after the widget has been bootstrapped with BotStarApi('boot') to programmatically open the chat window (mode must be 'livechat' or 'popup'). | | `BOTSTAR_LIVECHAT_UPDATE` | Livechat update | Tool to update user details on the current live chat session. Use when you need to modify user profile attributes during an active conversation. | | `BOTSTAR_PUBLISH_BOT` | Publish Bot to Live | Tool to publish a bot to live. Use when you need to deploy changes to the production environment. | | `BOTSTAR_UPDATE_BOT_ATTRIBUTE` | Update Bot Attribute | Tool to update a bot attribute in BotStar. Use when you need to modify the description or value of a bot attribute with optional multilingual support. | | `BOTSTAR_UPDATE_CMS_ENTITY` | Update CMS Entity | Tool to update a CMS entity in BotStar. Use when you need to modify the name or configuration of an existing CMS entity. | | `BOTSTAR_UPDATE_ENTITY_FIELDS` | Update Entity Fields | Tool to update entity field(s) in BotStar CMS. Use when you need to modify the name or options of existing fields. | | `BOTSTAR_UPDATE_ENTITY_ITEM` | Update Entity Item | Tool to update a CMS entity item in BotStar. Use when you need to modify the name, status, or custom field values of an entity item. | | `BOTSTAR_WEBVIEW_GET_PARAMETER` | Get BotStar Webview Parameter | Tool to retrieve a parameter value passed from the BotStar chatbot to the webview. Use inside onChatBotReady after your page loads in modal mode with bs:input meta tags. | | `BOTSTAR_WEBVIEW_SEND_RESPONSE` | Webview send response | Tool to send data from the webview back to the BotStar chatbot. Use when you need to transmit responses or custom outputs from an open webview. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Botstar MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Botstar. Instead of manually wiring Botstar 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 Botstar 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 Botstar 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 Botstar 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 Botstar 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 Botstar session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["botstar"] ) 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 Botstar 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 Botstar assistant agent with MCP tools agent = AssistantAgent( name="botstar_assistant", description="An AI assistant that helps with Botstar 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 Botstar 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 Botstar 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 Botstar session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["botstar"] ) 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 Botstar assistant agent with MCP tools agent = AssistantAgent( name="botstar_assistant", description="An AI assistant that helps with Botstar 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 Botstar 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 Botstar 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 Botstar, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Botstar MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/botstar/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/botstar/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/botstar/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/botstar/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/botstar/framework/codex) - [OpenClaw](https://composio.dev/toolkits/botstar/framework/openclaw) - [Hermes](https://composio.dev/toolkits/botstar/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/botstar/framework/cli) - [Google ADK](https://composio.dev/toolkits/botstar/framework/google-adk) - [LangChain](https://composio.dev/toolkits/botstar/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/botstar/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/botstar/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/botstar/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/botstar/framework/crew-ai) ## Related Toolkits - [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools. - [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations. - [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates. - [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates. - [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. It helps businesses automate support and streamline interactions through natural, voice-powered conversations. - [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code. - [Callerapi](https://composio.dev/toolkits/callerapi) - CallerAPI is a white-label caller identification platform for branded caller ID and fraud prevention. It helps businesses boost customer trust while stopping spam, fraud, and robocalls. - [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources. - [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates. - [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly. - [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time. - [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows. - [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment. - [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality. - [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster. - [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment. - [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support. - [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach. - [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback. - [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Botstar MCP? With a standalone Botstar MCP server, the agents and LLMs can only access a fixed set of Botstar tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Botstar 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 Botstar tools. ### Can I manage the permissions and scopes for Botstar while using Tool Router? Yes, absolutely. You can configure which Botstar 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 Botstar data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)