# How to integrate The odds api MCP with Autogen ```json { "title": "How to integrate The odds api MCP with Autogen", "toolkit": "The odds api", "toolkit_slug": "the_odds_api", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/the_odds_api/framework/autogen", "markdown_url": "https://composio.dev/toolkits/the_odds_api/framework/autogen.md", "updated_at": "2026-05-12T10:28:23.247Z" } ``` ## Introduction This guide walks you through connecting The odds api to AutoGen using the Composio tool router. By the end, you'll have a working The odds api agent that can show live nba game odds right now, list upcoming soccer matches this weekend, get current scores for mlb games through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a The odds api account through Composio's The odds api MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate The odds api with - [OpenAI Agents SDK](https://composio.dev/toolkits/the_odds_api/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/the_odds_api/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/the_odds_api/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/the_odds_api/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/the_odds_api/framework/codex) - [OpenClaw](https://composio.dev/toolkits/the_odds_api/framework/openclaw) - [Hermes](https://composio.dev/toolkits/the_odds_api/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/the_odds_api/framework/cli) - [Google ADK](https://composio.dev/toolkits/the_odds_api/framework/google-adk) - [LangChain](https://composio.dev/toolkits/the_odds_api/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/the_odds_api/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/the_odds_api/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/the_odds_api/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/the_odds_api/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 The odds api - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call The odds api tools - Run a live chat loop where you ask the agent to perform The odds api 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 The odds api MCP server, and what's possible with it? The The odds api MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your The odds api account. It provides structured and secure access to real-time sports betting odds and event data, so your agent can look up live odds, fetch sports schedules, track scores, and analyze betting markets worldwide on your behalf. - Live odds retrieval for events: Instantly fetch up-to-date betting odds for specific games or matches across multiple bookmakers and markets. - Comprehensive sports and event discovery: Ask your agent to list current and upcoming sporting events, including which sports are in season and event-specific details. - Participant and team lookups: Easily get information about teams, players, or participants involved in any listed sport to inform your analysis or predictions. - Live and recent score tracking: Stay up to date with real-time scores and recently completed game results for your favorite sports. - Regional and market-based odds filtering: Compare odds for specific regions, bookmakers, or betting markets to find the best opportunities. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `THE_ODDS_API_GET_EVENT_MARKETS` | Get Event Markets | Tool to retrieve available market keys for each bookmaker for a specific event. Returns only recently seen markets - not a comprehensive list. More markets become available as the event's commence time approaches. | | `THE_ODDS_API_GET_EVENT_ODDS` | Get Event Odds | Tool to retrieve odds for a specific event. Use after confirming sport key via THE_ODDS_API_GET_SPORTS and event ID via THE_ODDS_API_GET_EVENTS; mismatched values return empty payloads rather than errors. | | `THE_ODDS_API_GET_EVENTS` | Get Events | Tool to fetch live and upcoming events for a specified sport. Use when you need event listings including odds. All timestamps are UTC. Avoid high-frequency polling; batch requests and implement backoff to prevent throttling. | | `THE_ODDS_API_GET_ODDS` | Get Odds | Tool to fetch live and upcoming event odds for a specified sport, including bookmakers, regions, and markets. Use after retrieving sports via GET_SPORTS; filter by region, market, or event IDs. Response is nested bookmakers → markets → outcomes; not all bookmakers expose every market for every event, so handle missing keys and empty arrays defensively. Combining multiple regions, markets, and eventIds produces large payloads — narrow to one region or specific eventIds where possible. | | `THE_ODDS_API_GET_PARTICIPANTS` | Get Participants | Tool to fetch list of participants (teams or players) for a specified sport. Use after confirming you have a valid sport key. | | `THE_ODDS_API_GET_SCORES` | Get Scores | Tool to return live and recently completed event scores for a sport. Use after selecting a sport key to inspect current and recent game scores. Missing results may indicate unsupported competitions, not absent events. When identifying specific fixtures, match by both team names and date to avoid confusion with multi-leg ties or similarly named teams. | | `THE_ODDS_API_GET_SPORTS` | Get Sports | Tool to retrieve a list of in-season sports. Use when you need sports data; set 'all' to true to include out-of-season sports. Sport keys returned here must be passed to downstream tools like THE_ODDS_API_GET_EVENTS and THE_ODDS_API_GET_EVENT_ODDS — mismatched or guessed keys return empty payloads. Similarly named leagues and qualifier competitions appear as distinct entries with unique keys; verify the exact key before use. | | `THE_ODDS_API_GET_V3_ODDS` | Get Odds (V3 Legacy) | Tool to fetch odds using the legacy V3 API endpoint. Returns upcoming and live games with odds for a given sport, region, and market. Use for legacy integrations; V4 API is recommended for new implementations. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The The odds api MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to The odds api. Instead of manually wiring The odds api 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 The odds api 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 The odds api 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 The odds api 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 The odds api 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 The odds api session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["the_odds_api"] ) 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 The odds api 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 The odds api assistant agent with MCP tools agent = AssistantAgent( name="the_odds_api_assistant", description="An AI assistant that helps with The odds api 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 The odds api 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 The odds api 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 The odds api session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["the_odds_api"] ) 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 The odds api assistant agent with MCP tools agent = AssistantAgent( name="the_odds_api_assistant", description="An AI assistant that helps with The odds api 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 The odds api 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 The odds api 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 The odds api, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build The odds api MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/the_odds_api/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/the_odds_api/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/the_odds_api/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/the_odds_api/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/the_odds_api/framework/codex) - [OpenClaw](https://composio.dev/toolkits/the_odds_api/framework/openclaw) - [Hermes](https://composio.dev/toolkits/the_odds_api/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/the_odds_api/framework/cli) - [Google ADK](https://composio.dev/toolkits/the_odds_api/framework/google-adk) - [LangChain](https://composio.dev/toolkits/the_odds_api/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/the_odds_api/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/the_odds_api/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/the_odds_api/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/the_odds_api/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and The odds api MCP? With a standalone The odds api MCP server, the agents and LLMs can only access a fixed set of The odds api tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from The odds api 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 The odds api tools. ### Can I manage the permissions and scopes for The odds api while using Tool Router? Yes, absolutely. You can configure which The odds api 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 The odds api data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)