# How to integrate The odds api MCP with Pydantic AI ```json { "title": "How to integrate The odds api MCP with Pydantic AI", "toolkit": "The odds api", "toolkit_slug": "the_odds_api", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/the_odds_api/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/the_odds_api/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:28:23.247Z" } ``` ## Introduction This guide walks you through connecting The odds api to Pydantic AI 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 Pydantic AI 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: - How to set up your Composio API key and User ID - How to create a Composio Tool Router session for The odds api - How to attach an MCP Server to a Pydantic AI agent - How to stream responses and maintain chat history - How to build a simple REPL-style chat interface to test your The odds api workflows ## What is Pydantic AI? Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications. Key features include: - Type Safety: Built on Pydantic for automatic data validation - MCP Support: Native support for Model Context Protocol servers - Streaming: Built-in support for streaming responses - Async First: Designed for async/await patterns ## 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 agent to The odds api. It provides structured and secure access so your agent can perform The odds api operations on your behalf through a secure, permission-based interface. 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 Before starting, make sure you have: - Python 3.9 or higher - A Composio account with an active API key - Basic familiarity with Python and async programming ### 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 the required libraries. What's happening: - composio connects your agent to external SaaS tools like The odds api - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your agent to Composio's API - USER_ID associates your session with your account for secure tool access - OPENAI_API_KEY to access OpenAI LLMs ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to The odds api - MCPServerStreamableHTTP connects to the The odds api MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() ``` ### 5. Create a Tool Router Session What's happening: - We're creating a Tool Router session that gives your agent access to The odds api tools - The create method takes the user ID and specifies which toolkits should be available - The returned session.mcp.url is the MCP server URL that your agent will use ```python async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for The odds api composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["the_odds_api"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the The odds api endpoint - The agent uses GPT-5 to interpret user commands and perform The odds api operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent the_odds_api_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[the_odds_api_mcp], instructions=( "You are a The odds api assistant. Use The odds api tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - The odds api API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```python # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with The odds api.\n") 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", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for The odds api composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["the_odds_api"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") # Attach the MCP server to a Pydantic AI Agent the_odds_api_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[the_odds_api_mcp], instructions=( "You are a The odds api assistant. Use The odds api tools to help users " "with their requests. Ask clarifying questions when needed." ), ) # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with The odds api.\n") 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", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You've built a Pydantic AI agent that can interact with The odds api through Composio's Tool Router. With this setup, your agent can perform real The odds api actions through natural language. You can extend this further by: - Adding other toolkits like Gmail, HubSpot, or Salesforce - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + The odds api for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## 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 Pydantic AI? Yes, you can. Pydantic AI 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)