# How to integrate Mopinion MCP with Autogen ```json { "title": "How to integrate Mopinion MCP with Autogen", "toolkit": "Mopinion", "toolkit_slug": "mopinion", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/mopinion/framework/autogen", "markdown_url": "https://composio.dev/toolkits/mopinion/framework/autogen.md", "updated_at": "2026-05-12T10:19:29.427Z" } ``` ## Introduction This guide walks you through connecting Mopinion to AutoGen using the Composio tool router. By the end, you'll have a working Mopinion agent that can get all recent website feedback reports, summarize negative feedback from mobile users, list most common survey responses this week through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Mopinion account through Composio's Mopinion MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Mopinion with - [OpenAI Agents SDK](https://composio.dev/toolkits/mopinion/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/mopinion/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/mopinion/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/mopinion/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/mopinion/framework/codex) - [OpenClaw](https://composio.dev/toolkits/mopinion/framework/openclaw) - [Hermes](https://composio.dev/toolkits/mopinion/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/mopinion/framework/cli) - [Google ADK](https://composio.dev/toolkits/mopinion/framework/google-adk) - [LangChain](https://composio.dev/toolkits/mopinion/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/mopinion/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/mopinion/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/mopinion/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/mopinion/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 Mopinion - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Mopinion tools - Run a live chat loop where you ask the agent to perform Mopinion 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 Mopinion MCP server, and what's possible with it? The Mopinion MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Mopinion account. It provides structured and secure access to your feedback data and analytics, so your agent can perform actions like retrieving user feedback, analyzing survey results, generating reports, and monitoring trends on your behalf. - Centralized feedback retrieval: Instantly pull user feedback from all your websites and apps so your agent can surface insights across every touchpoint. - Survey results analysis: Let your agent analyze form and survey submissions, identifying common issues, sentiment, and emerging trends. - Custom report generation: Have the agent generate detailed feedback reports, aggregating user responses and highlighting actionable improvements. - Trend and KPI monitoring: Ask your agent to track changes in user sentiment or conversion-related metrics over time for continuous optimization. - Segmented feedback filtering: Enable your agent to filter and group feedback by device, location, or other custom attributes to uncover targeted opportunities. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `MOPINION_GET_ACCOUNT` | Get Account | Tool to retrieve the current authenticated account information. Use to verify authentication and get account details. | | `MOPINION_GET_DATASET_BY_ID` | Get Dataset by ID | Retrieve complete metadata for a specific Mopinion dataset (feedback form) by its ID. Returns dataset properties including name, associated report ID, data source type, and description. Use this action when you need detailed information about a specific dataset/form. To discover available dataset IDs, use the List Datasets action first. This is a read-only operation that does not modify any data. | | `MOPINION_GET_DATASET_FEEDBACK` | Get Dataset Feedback | Retrieve feedback items (survey responses) for a specific dataset/form with optional pagination and filtering. Use this action to fetch multiple feedback entries from a dataset. Each feedback item contains the survey responses including custom fields, scores, metadata, and timestamps. Supports pagination for large result sets and filtering by field values. For retrieving a single feedback item by ID, use GET_DATASET_FEEDBACK_BY_ID instead. | | `MOPINION_GET_DATASET_FEEDBACK_BY_ID` | Get Dataset Feedback By ID | Retrieves a single feedback item by its unique identifier from a specific dataset. Use this tool when you need detailed information about a specific feedback item. First obtain the dataset_id using List Datasets, then get feedback_id values using Get Dataset Feedback. **Important Notes:** - Returns a warning in metadata if the feedback item doesn't exist (with null field values) - Returns 404 error if the dataset_id itself is invalid or inaccessible - The response includes feedback fields, tags, scores, timestamps, and associated metadata | | `MOPINION_GET_DATASET_FIELDS` | Get Dataset Field Definitions | Tool to retrieve field definitions for a dataset. Use when you need the schema of a dataset's fields. | | `MOPINION_GET_DEPLOYMENT_BY_ID` | Get Deployment by ID | Retrieves detailed configuration for a specific feedback form deployment by its ID. Returns deployment rules, trigger conditions, scheduling settings, target URLs, and active status. Use this to understand when, where, and how a feedback form is displayed to users. | | `MOPINION_GET_DEPLOYMENTS` | Get Deployments | Tool to list all deployments for the authenticated Mopinion account. Use after setting up authentication. | | `MOPINION_GET_REPORT_BY_ID` | Get Report By ID | Retrieves detailed information about a specific Mopinion report by its ID. Returns comprehensive report details including name, description, language, creation date, and all associated datasets with their metadata. Use this when you need full information about a specific report. To find available report IDs, use the Get Reports action first. Example use case: Get complete details of report 22511 to understand its datasets and configuration. | | `MOPINION_GET_REPORT_FEEDBACK` | Get Report Feedback | Tool to retrieve feedback items for a report. Use when you need paginated and filtered feedback entries for analysis. | | `MOPINION_GET_REPORT_FIELDS` | Get Report Fields | Tool to retrieve field definitions for a specific report. Use when you need the schema of a report's feedback fields before constructing or analyzing forms. | | `MOPINION_GET_ROOT` | Get API Root | Check Mopinion API availability and get version information. Pings the API health check endpoint (/ping) and returns status code, 'pong' response, and current API version. Use this to verify the API is reachable and operational. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Mopinion MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Mopinion. Instead of manually wiring Mopinion 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 Mopinion 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 Mopinion 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 Mopinion 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 Mopinion 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 Mopinion session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["mopinion"] ) 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 Mopinion 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 Mopinion assistant agent with MCP tools agent = AssistantAgent( name="mopinion_assistant", description="An AI assistant that helps with Mopinion 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 Mopinion 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 Mopinion 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 Mopinion session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["mopinion"] ) 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 Mopinion assistant agent with MCP tools agent = AssistantAgent( name="mopinion_assistant", description="An AI assistant that helps with Mopinion 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 Mopinion 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 Mopinion 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 Mopinion, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Mopinion MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/mopinion/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/mopinion/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/mopinion/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/mopinion/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/mopinion/framework/codex) - [OpenClaw](https://composio.dev/toolkits/mopinion/framework/openclaw) - [Hermes](https://composio.dev/toolkits/mopinion/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/mopinion/framework/cli) - [Google ADK](https://composio.dev/toolkits/mopinion/framework/google-adk) - [LangChain](https://composio.dev/toolkits/mopinion/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/mopinion/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/mopinion/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/mopinion/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/mopinion/framework/crew-ai) ## Related Toolkits - [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. 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It helps you quickly gather, track, and act on customer sentiment. - [Dovetail](https://composio.dev/toolkits/dovetail) - Dovetail is a research analysis platform for transcript review and insight generation. It helps teams code interviews, analyze feedback, and create actionable research summaries. - [Dub](https://composio.dev/toolkits/dub) - Dub is a short link management platform with analytics and API access. Use it to easily create, manage, and track branded short links for your business. - [Elasticsearch](https://composio.dev/toolkits/elasticsearch) - Elasticsearch is a distributed, RESTful search and analytics engine for all types of data. It delivers fast, scalable search and powerful analytics across massive datasets. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Mopinion MCP? With a standalone Mopinion MCP server, the agents and LLMs can only access a fixed set of Mopinion tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Mopinion 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 Mopinion tools. ### Can I manage the permissions and scopes for Mopinion while using Tool Router? Yes, absolutely. You can configure which Mopinion 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 Mopinion data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)