# How to integrate Segment MCP with Autogen ```json { "title": "How to integrate Segment MCP with Autogen", "toolkit": "Segment", "toolkit_slug": "segment", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/segment/framework/autogen", "markdown_url": "https://composio.dev/toolkits/segment/framework/autogen.md", "updated_at": "2026-05-12T10:25:03.502Z" } ``` ## Introduction This guide walks you through connecting Segment to AutoGen using the Composio tool router. By the end, you'll have a working Segment agent that can fetch daily api usage for each source, add metadata labels to a specific source, identify a user and update their traits through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Segment account through Composio's Segment MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Segment with - [OpenAI Agents SDK](https://composio.dev/toolkits/segment/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/segment/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/segment/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/segment/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/segment/framework/codex) - [OpenClaw](https://composio.dev/toolkits/segment/framework/openclaw) - [Hermes](https://composio.dev/toolkits/segment/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/segment/framework/cli) - [Google ADK](https://composio.dev/toolkits/segment/framework/google-adk) - [LangChain](https://composio.dev/toolkits/segment/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/segment/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/segment/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/segment/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/segment/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 Segment - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Segment tools - Run a live chat loop where you ask the agent to perform Segment 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 Segment MCP server, and what's possible with it? The Segment MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Segment account. It provides structured and secure access to your customer data platform, so your agent can perform actions like identifying users, tracking analytics events, managing sources and destinations, and monitoring API usage on your behalf. - User identification and trait management: Your agent can identify users, set or update their traits, and manage user profiles using Segment's Identify and Group tools. - Analytics event tracking and batching: Effortlessly track individual or batched analytics events, enabling automated insights and seamless event monitoring across platforms. - Source and destination administration: Let your agent add labels to sources, delete sources, retrieve detailed destination configurations, and list warehouses connected to a source. - Alias and merge user identities: Merge anonymous and known identities by aliasing user IDs for more accurate customer journeys and unified profiles. - Usage monitoring and delivery metrics: Fetch daily API call usage per source and view delivery metrics summaries for destinations to keep tabs on system health and integration performance. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SEGMENT_ADD_LABELS_TO_SOURCE` | Add Labels to Source | Tool to add existing labels to a Source. Use when you have the source ID and want to tag it with metadata labels. | | `SEGMENT_ALIAS` | Segment Alias | Tool to alias a previous user ID to a new user ID. Use when merging anonymous and known identities. | | `SEGMENT_BATCH` | Batch Segment Analytics Events | Tool to send multiple analytics calls in a single batch request. Use when you want to reduce HTTP overhead by batching Identify/Track/Page/Screen/Group calls into one request. | | `SEGMENT_DELETE_SOURCE` | Delete Source | Tool to delete a Segment Source. Use when you need to permanently remove a Source by its ID after confirmation. | | `SEGMENT_GET_DAILY_PER_SOURCE_API_CALLS_USAGE` | Get Daily Per Source API Calls Usage | Tool to fetch daily API call counts per source for a given period. Use when you need daily breakdown of API usage by source after determining the reporting period. | | `SEGMENT_GET_DESTINATION` | Get Destination | Tool to retrieve a Destination by ID. Use when you need to fetch the full configuration of a Segment Destination instance by its unique identifier. Falls back US→EU public API and legacy app endpoint; returns minimal envelope on legacy HTML or parse errors. | | `SEGMENT_GROUP` | Segment Group | Tool to associate an identified user with a group via Segment HTTP Tracking API. Use when grouping users with traits. | | `SEGMENT_IDENTIFY` | Segment Identify | Tool to identify a user and set/update traits via Segment HTTP Tracking API. | | `SEGMENT_IMPORT_HISTORICAL_DATA` | Import Historical Data | Tool to import historical data in bulk with support for historical timestamps. Use when you need to backfill or import past events with their original timestamps into Segment. | | `SEGMENT_LIST_CONNECTED_WAREHOUSES_FROM_SOURCE` | List Connected Warehouses From Source | Tool to list warehouses connected to a Source. Use when you need to retrieve warehouses for a given source ID. | | `SEGMENT_LIST_DELIVERY_METRICS_SUMMARY_FROM_DESTINATION` | List Delivery Metrics Summary from Destination | Get an event delivery metrics summary from a Destination. Primary attempt uses Segment Public API; fallback to legacy app host if needed. On HTML fallback responses, returns a minimal valid envelope to maintain contract. | | `SEGMENT_LIST_SCHEMA_SETTINGS_IN_SOURCE` | List Schema Settings in Source | Retrieve schema configuration settings for a Source. | | `SEGMENT_PAGE` | Segment Page View | Tool to record a page view via Segment HTTP Tracking API. Use when sending page views with optional page name and properties. | | `SEGMENT_REMOVE_SOURCE_WRITE_KEY` | Remove Source Write Key | Tool to remove a write key from a Source. Use when you need to revoke an existing write key for security or rotation. | | `SEGMENT_SCREEN` | Segment Screen Event | Tool to record a mobile app screen view. Use when tracking screen views in a mobile app via Segment HTTP Tracking API. | | `SEGMENT_TRACK` | Segment Track Event | Tool to record a custom user event via Segment HTTP Tracking API. Use when sending events to Segment with valid identity. | | `SEGMENT_UPDATE_SOURCE` | Update Source | Tool to update a Source's metadata and settings. Use when you need to modify an existing Source after confirming its ID. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Segment MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Segment. Instead of manually wiring Segment 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 Segment 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 Segment 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 Segment 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 Segment 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 Segment session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["segment"] ) 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 Segment 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 Segment assistant agent with MCP tools agent = AssistantAgent( name="segment_assistant", description="An AI assistant that helps with Segment 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 Segment 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 Segment 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 Segment session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["segment"] ) 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 Segment assistant agent with MCP tools agent = AssistantAgent( name="segment_assistant", description="An AI assistant that helps with Segment 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 Segment 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 Segment 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 Segment, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Segment MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/segment/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/segment/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/segment/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/segment/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/segment/framework/codex) - [OpenClaw](https://composio.dev/toolkits/segment/framework/openclaw) - [Hermes](https://composio.dev/toolkits/segment/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/segment/framework/cli) - [Google ADK](https://composio.dev/toolkits/segment/framework/google-adk) - [LangChain](https://composio.dev/toolkits/segment/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/segment/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/segment/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/segment/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/segment/framework/crew-ai) ## Related Toolkits - [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources. - [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research. - [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows. - [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research. - [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data. - [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds. - [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights. - [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly. - [Bright Data MCP](https://composio.dev/toolkits/brightdata_mcp) - Bright Data MCP is an AI-powered web scraping and data collection platform. Instantly access public web data in real time with advanced scraping tools. - [Browseai](https://composio.dev/toolkits/browseai) - Browseai is a web automation and data extraction platform that turns any website into an API. It's perfect for monitoring websites and retrieving structured data without manual scraping. - [ClickHouse](https://composio.dev/toolkits/clickhouse) - ClickHouse is an open-source, column-oriented database for real-time analytics and big data processing using SQL. Its lightning-fast query performance makes it ideal for handling large datasets and delivering instant insights. - [Coinmarketcal](https://composio.dev/toolkits/coinmarketcal) - CoinMarketCal is a community-powered crypto calendar for upcoming events, announcements, and releases. It helps traders track market-moving developments and stay ahead in the crypto space. - [Control d](https://composio.dev/toolkits/control_d) - Control d is a customizable DNS filtering and traffic redirection platform. It helps you manage internet access, enforce policies, and monitor usage across devices and networks. - [Databox](https://composio.dev/toolkits/databox) - Databox is a business analytics platform that connects your data from any tool and device. It helps you track KPIs, build dashboards, and discover actionable insights. - [Databricks](https://composio.dev/toolkits/databricks) - Databricks is a unified analytics platform for big data and AI on the lakehouse architecture. It empowers data teams to collaborate, analyze, and build scalable solutions efficiently. - [Datagma](https://composio.dev/toolkits/datagma) - Datagma delivers data intelligence and analytics for business growth and market discovery. Get actionable market insights and track competitors to inform your strategy. - [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. - [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 Segment MCP? With a standalone Segment MCP server, the agents and LLMs can only access a fixed set of Segment tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Segment 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 Segment tools. ### Can I manage the permissions and scopes for Segment while using Tool Router? Yes, absolutely. You can configure which Segment 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 Segment data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)