# How to integrate Linguapop MCP with Autogen ```json { "title": "How to integrate Linguapop MCP with Autogen", "toolkit": "Linguapop", "toolkit_slug": "linguapop", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/linguapop/framework/autogen", "markdown_url": "https://composio.dev/toolkits/linguapop/framework/autogen.md", "updated_at": "2026-05-12T10:17:38.101Z" } ``` ## Introduction This guide walks you through connecting Linguapop to AutoGen using the Composio tool router. By the end, you'll have a working Linguapop agent that can show all languages available for testing, check if italian is supported for placement, list every language students can choose through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Linguapop account through Composio's Linguapop MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Linguapop with - [OpenAI Agents SDK](https://composio.dev/toolkits/linguapop/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/linguapop/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/linguapop/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/linguapop/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/linguapop/framework/codex) - [OpenClaw](https://composio.dev/toolkits/linguapop/framework/openclaw) - [Hermes](https://composio.dev/toolkits/linguapop/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/linguapop/framework/cli) - [Google ADK](https://composio.dev/toolkits/linguapop/framework/google-adk) - [LangChain](https://composio.dev/toolkits/linguapop/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/linguapop/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/linguapop/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/linguapop/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/linguapop/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 Linguapop - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Linguapop tools - Run a live chat loop where you ask the agent to perform Linguapop 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 Linguapop MCP server, and what's possible with it? The Linguapop MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Linguapop account. It provides structured and secure access to language placement test data, so your agent can retrieve supported languages, prepare test workflows, and streamline test administration on your behalf. - Retrieve available test languages: Instantly fetch the list of languages supported by Linguapop to ensure accurate placement and test planning. - Validate language support prior to testing: Have your agent confirm whether a specific language is available for placement tests before assigning or scheduling exams. - Automate test setup workflows: Let your agent check supported languages and prepare the necessary resources for candidates or classes without manual intervention. - Dynamic multilingual experience management: Seamlessly adapt testing options for students or staff based on real-time language availability from Linguapop. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `LINGUAPOP_FETCH_AVAILABLE_LANGUAGES` | Fetch Available Languages | Tool to retrieve the list of available languages. Use when you need to verify supported languages before starting a placement test. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Linguapop MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Linguapop. Instead of manually wiring Linguapop 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 Linguapop 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 Linguapop 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 Linguapop 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 Linguapop 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 Linguapop session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["linguapop"] ) 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 Linguapop 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 Linguapop assistant agent with MCP tools agent = AssistantAgent( name="linguapop_assistant", description="An AI assistant that helps with Linguapop 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 Linguapop 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 Linguapop 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 Linguapop session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["linguapop"] ) 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 Linguapop assistant agent with MCP tools agent = AssistantAgent( name="linguapop_assistant", description="An AI assistant that helps with Linguapop 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 Linguapop 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 Linguapop 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 Linguapop, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Linguapop MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/linguapop/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/linguapop/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/linguapop/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/linguapop/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/linguapop/framework/codex) - [OpenClaw](https://composio.dev/toolkits/linguapop/framework/openclaw) - [Hermes](https://composio.dev/toolkits/linguapop/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/linguapop/framework/cli) - [Google ADK](https://composio.dev/toolkits/linguapop/framework/google-adk) - [LangChain](https://composio.dev/toolkits/linguapop/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/linguapop/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/linguapop/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/linguapop/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/linguapop/framework/crew-ai) ## Related Toolkits - [Canvas](https://composio.dev/toolkits/canvas) - Canvas is a learning management system for online courses, assignments, grading, and collaboration. It's trusted by educators and students to streamline virtual classrooms and enhance digital learning. - [Accredible certificates](https://composio.dev/toolkits/accredible_certificates) - Accredible Certificates is a platform for creating and managing digital certificates, badges, and blockchain credentials. It streamlines issuing, tracking, and verifying professional achievements for organizations of any size. - [Api bible](https://composio.dev/toolkits/api_bible) - API.Bible is a developer platform for Scripture content and passage search. Easily integrate Bible verses and translations into your apps or chatbots. - [Blackboard](https://composio.dev/toolkits/blackboard) - Blackboard is a digital learning platform for higher education and schools, offering tools to manage courses, track engagement, and deliver interactive content. It helps institutions improve student outcomes through actionable analytics and in-app guidance. - [Certifier](https://composio.dev/toolkits/certifier) - Certifier is a platform for creating, managing, and issuing digital certificates and credentials. Organizations use it to automate and secure the entire credentialing process. - [Classmarker](https://composio.dev/toolkits/classmarker) - ClassMarker is a professional online quiz maker for business and education. It provides instant grading, flexible test design, and in-depth reporting. - [Coassemble](https://composio.dev/toolkits/coassemble) - Coassemble is a flexible platform for building, managing, and delivering online training courses. It helps teams streamline onboarding, upskilling, and ongoing learning for employees or partners. - [D2lbrightspace](https://composio.dev/toolkits/d2lbrightspace) - D2L Brightspace is a learning management system for delivering and managing online courses and assessments. It helps educators streamline digital teaching, assignments, and communication with students. - [Dictionary api](https://composio.dev/toolkits/dictionary_api) - Dictionary api is the Merriam-Webster API providing rich dictionary and thesaurus data for developers. Instantly access definitions, synonyms, etymologies, and audio pronunciations in your apps. - [Google Classroom](https://composio.dev/toolkits/google_classroom) - Google Classroom is a free web service for educators and students to manage assignments and communication. It streamlines classroom collaboration and grading, making teaching simpler and more connected. - [Lessonspace](https://composio.dev/toolkits/lessonspace) - Lessonspace is an online collaborative classroom platform offering video, whiteboards, and real-time interaction for educators and students. It streamlines remote teaching with integrated tools for engagement and communication. - [Memberspot](https://composio.dev/toolkits/memberspot) - Memberspot is an online course and video-hosting platform for business learning. It helps teams manage, deliver, and track knowledge efficiently. - [Membervault](https://composio.dev/toolkits/membervault) - Membervault is a platform for hosting courses, memberships, and digital products in one place. It helps you build stronger relationships with your audience by centralizing digital offers and customer engagement. - [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. - [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options. - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [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. - [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide. - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Linguapop MCP? With a standalone Linguapop MCP server, the agents and LLMs can only access a fixed set of Linguapop tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Linguapop 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 Linguapop tools. ### Can I manage the permissions and scopes for Linguapop while using Tool Router? Yes, absolutely. You can configure which Linguapop 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 Linguapop data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)