# How to integrate Detrack MCP with Autogen ```json { "title": "How to integrate Detrack MCP with Autogen", "toolkit": "Detrack", "toolkit_slug": "detrack", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/detrack/framework/autogen", "markdown_url": "https://composio.dev/toolkits/detrack/framework/autogen.md", "updated_at": "2026-05-06T08:08:27.653Z" } ``` ## Introduction This guide walks you through connecting Detrack to AutoGen using the Composio tool router. By the end, you'll have a working Detrack agent that can list all deliveries scheduled for today, edit delivery details for a specific order, view all vehicles in your fleet through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Detrack account through Composio's Detrack MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Detrack with - [OpenAI Agents SDK](https://composio.dev/toolkits/detrack/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/detrack/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/detrack/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/detrack/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/detrack/framework/codex) - [OpenClaw](https://composio.dev/toolkits/detrack/framework/openclaw) - [Hermes](https://composio.dev/toolkits/detrack/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/detrack/framework/cli) - [Google ADK](https://composio.dev/toolkits/detrack/framework/google-adk) - [LangChain](https://composio.dev/toolkits/detrack/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/detrack/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/detrack/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/detrack/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/detrack/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 Detrack - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Detrack tools - Run a live chat loop where you ask the agent to perform Detrack 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 Detrack MCP server, and what's possible with it? The Detrack MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Detrack account. It provides structured and secure access to your delivery management system, so your agent can perform actions like tracking deliveries, managing jobs, editing or deleting jobs, and viewing vehicles on your behalf. - Real-time delivery and collection management: Instantly create, edit, or delete delivery and collection jobs, letting your agent keep your schedules and records up to date. - Comprehensive job search and filtering: Ask your agent to search for deliveries, collections, or vehicles with flexible criteria—by date, status, country, and more. - Bulk actions for efficient operations: Direct your agent to delete all deliveries or collections for a specific date, making large-scale updates a breeze. - Fleet visibility and vehicle management: Retrieve a complete list of all your vehicles, so your agent can help with asset tracking and resource planning. - Detailed job listing and reporting: Let your agent fetch and summarize all jobs or collections, providing daily overviews and insights for your logistics workflow. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `DETRACK_ADD_COLLECTION` | Add Collection | Tool to add a new collection in detrack. use after gathering all necessary collection details. | | `DETRACK_DELETE_ALL_COLLECTIONS` | Delete All Collections | Tool to delete all collections in the account. use when you need to purge every collection for a specific date after confirmation. | | `DETRACK_DELETE_ALL_DELIVERIES` | Delete All Deliveries | Tool to delete all deliveries for a specific date. use when you need to purge deliveries in bulk before scheduling new ones. | | `DETRACK_DELETE_DELIVERY` | Delete Delivery | Tool to delete one or more deliveries by date and d.o. number. use after confirming delivery entries to avoid accidental data loss (max 100 items per call). | | `DETRACK_EDIT_DELIVERY` | Edit Delivery | Tool to edit specific deliveries by date and d.o. number. use after confirming delivery identifiers to update their details (max 100 per call). | | `DETRACK_LIST_JOBS` | List Jobs | Tool to list all jobs with optional filters and pagination. use when you need to retrieve jobs by date, status, country, or other criteria. | | `DETRACK_SEARCH` | Search | Tool to search for deliveries, collections, or vehicles. use after defining search criteria to retrieve matching jobs. | | `DETRACK_VIEW_ALL_COLLECTIONS` | View All Collections | Tool to view all collection jobs in detrack. use when you need to retrieve every collection job currently stored. | | `DETRACK_VIEW_ALL_DELIVERIES` | View All Deliveries | Tool to view all deliveries for a specific date. use when you need to retrieve all delivery jobs on a given date. | | `DETRACK_VIEW_ALL_VEHICLES` | View All Vehicles | Tool to view all vehicles in the account. use when you need a complete list of your fleet with optional pagination. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Detrack MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Detrack. Instead of manually wiring Detrack 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 Detrack 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 Detrack 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 Detrack 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 Detrack 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 Detrack session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["detrack"] ) 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 Detrack 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 Detrack assistant agent with MCP tools agent = AssistantAgent( name="detrack_assistant", description="An AI assistant that helps with Detrack 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 Detrack 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 Detrack 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 Detrack session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["detrack"] ) 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 Detrack assistant agent with MCP tools agent = AssistantAgent( name="detrack_assistant", description="An AI assistant that helps with Detrack 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 Detrack 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 Detrack 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 Detrack, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Detrack MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/detrack/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/detrack/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/detrack/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/detrack/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/detrack/framework/codex) - [OpenClaw](https://composio.dev/toolkits/detrack/framework/openclaw) - [Hermes](https://composio.dev/toolkits/detrack/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/detrack/framework/cli) - [Google ADK](https://composio.dev/toolkits/detrack/framework/google-adk) - [LangChain](https://composio.dev/toolkits/detrack/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/detrack/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/detrack/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/detrack/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/detrack/framework/crew-ai) ## Related Toolkits - [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. 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However, with the Composio Tool Router, agents can dynamically load tools from Detrack 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 Detrack tools. ### Can I manage the permissions and scopes for Detrack while using Tool Router? Yes, absolutely. You can configure which Detrack 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 Detrack data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)