# How to integrate Beamer MCP with Autogen ```json { "title": "How to integrate Beamer MCP with Autogen", "toolkit": "Beamer", "toolkit_slug": "beamer", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/beamer/framework/autogen", "markdown_url": "https://composio.dev/toolkits/beamer/framework/autogen.md", "updated_at": "2026-05-12T10:02:40.328Z" } ``` ## Introduction This guide walks you through connecting Beamer to AutoGen using the Composio tool router. By the end, you'll have a working Beamer agent that can count the number of posts this month, fetch unread notifications for your account, list comments on the latest product update through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Beamer account through Composio's Beamer MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Beamer with - [OpenAI Agents SDK](https://composio.dev/toolkits/beamer/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/beamer/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/beamer/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/beamer/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/beamer/framework/codex) - [OpenClaw](https://composio.dev/toolkits/beamer/framework/openclaw) - [Hermes](https://composio.dev/toolkits/beamer/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/beamer/framework/cli) - [Google ADK](https://composio.dev/toolkits/beamer/framework/google-adk) - [LangChain](https://composio.dev/toolkits/beamer/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/beamer/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/beamer/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/beamer/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/beamer/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 Beamer - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Beamer tools - Run a live chat loop where you ask the agent to perform Beamer 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 Beamer MCP server, and what's possible with it? The Beamer MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Beamer account. It provides structured and secure access to your Beamer news posts, notifications, and categories, so your agent can perform actions like retrieving posts, counting updates, fetching notifications, and managing user engagement—all on your behalf. - Instant post retrieval and listing: Ask your agent to fetch the latest product updates or announcements, or list all posts with their IDs and titles for quick reference. - Engagement analytics and reactions: Have the agent pull post reaction data, so you can understand how users are responding to your news and updates. - Notification management: Let your agent retrieve unread notifications or fetch full details about specific notifications, helping you stay on top of user engagement in real time. - Comment and feedback access: Easily get all comments on a particular post, enabling you to review direct user feedback and respond accordingly. - Feed and category insights: Fetch personalized feed URLs or retrieve detailed information about categories to better segment and embed announcement streams for your users. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `BEAMER_COUNT_POST_COMMENTS` | Count Post Comments | Tool to count existing comments on a specific post. Use when you need the total number of comments matching specific filters. | | `BEAMER_COUNT_POST_REACTIONS` | Count Post Reactions | Tool to count existing reactions on a specific post. Use when you need the total number of reactions for a given post. | | `BEAMER_COUNT_POSTS` | Count Posts | Tool to count existing posts. Use when you need the number of posts matching specific filters. | | `BEAMER_COUNT_UNREAD_POSTS` | Count Unread Posts | Tool to count unread posts for a user. Use when you need the number of posts the user would see when opening their Beamer feed. | | `BEAMER_GET_CATEGORY` | Get Category | Tool to retrieve metadata for a Beamer category by its ID. Use when you need category information for filtering or grouping posts. Beamer uses a fixed set of categories: new, improvement, fix, comingsoon, announcement, and other. | | `BEAMER_GET_FEED` | Get Feed | Tool to retrieve the URL for your standalone feed. Use after embedding to fetch the feed link for embedding or sharing. | | `BEAMER_GET_NOTIFICATION` | Get Notification | Tool to retrieve details of a specific notification by its unique notification ID. Use after obtaining the notification ID to fetch its full details. | | `BEAMER_GET_NOTIFICATIONS` | Get Notifications | Tool to fetch unread notifications. Use after providing user context to retrieve and mark notifications as read. | | `BEAMER_GET_POST_COMMENTS` | Get Post Comments | Tool to retrieve comments for a specific post. Use after identifying the post ID to list its comments. | | `BEAMER_GET_POST_REACTIONS` | Get Post Reactions | Tool to retrieve all reactions associated with a specific post. Use when you need to list reactions and optionally filter by date, reaction type, or pagination. | | `BEAMER_GET_POSTS` | Get Posts | Tool to retrieve a list of posts. Use when you need IDs and titles of posts for further operations. | | `BEAMER_PING` | Ping API | Tool to ping the Beamer API. Use when verifying API key authentication before making further requests. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Beamer MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Beamer. Instead of manually wiring Beamer 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 Beamer 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 Beamer 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 Beamer 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 Beamer 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 Beamer session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["beamer"] ) 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 Beamer 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 Beamer assistant agent with MCP tools agent = AssistantAgent( name="beamer_assistant", description="An AI assistant that helps with Beamer 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 Beamer 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 Beamer 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 Beamer session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["beamer"] ) 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 Beamer assistant agent with MCP tools agent = AssistantAgent( name="beamer_assistant", description="An AI assistant that helps with Beamer 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 Beamer 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 Beamer 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 Beamer, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Beamer MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/beamer/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/beamer/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/beamer/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/beamer/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/beamer/framework/codex) - [OpenClaw](https://composio.dev/toolkits/beamer/framework/openclaw) - [Hermes](https://composio.dev/toolkits/beamer/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/beamer/framework/cli) - [Google ADK](https://composio.dev/toolkits/beamer/framework/google-adk) - [LangChain](https://composio.dev/toolkits/beamer/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/beamer/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/beamer/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/beamer/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/beamer/framework/crew-ai) ## Related Toolkits - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools. - [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools. - [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. - [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals. - [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams. - [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience. - [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs. - [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics. - [Doppler marketing automation](https://composio.dev/toolkits/doppler_marketing_automation) - Doppler marketing automation is a platform for creating, sending, and tracking email campaigns. It helps you automate marketing workflows and manage subscriber lists for better engagement. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Beamer MCP? With a standalone Beamer MCP server, the agents and LLMs can only access a fixed set of Beamer tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Beamer 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 Beamer tools. ### Can I manage the permissions and scopes for Beamer while using Tool Router? Yes, absolutely. You can configure which Beamer 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 Beamer data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)