# How to integrate The odds api MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate The odds api MCP with OpenAI Agents SDK",
  "toolkit": "The odds api",
  "toolkit_slug": "the_odds_api",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/the_odds_api/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/the_odds_api/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:28:23.247Z"
}
```

## Introduction

This guide walks you through connecting The odds api to the OpenAI Agents SDK 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 OpenAI Agents SDK 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

- [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 necessary dependencies
- Initialize Composio and create a Tool Router session for The odds api
- Configure an AI agent that can use The odds api as a tool
- Run a live chat session where you can ask the agent to perform The odds api operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

## 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:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live The odds api project
- Some knowledge of Python or Typescript

### 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).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like The odds api.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only the_odds_api.
- The router checks the user's The odds api connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access The odds api.
- This approach keeps things lightweight and lets the agent request The odds api tools only when needed during the conversation.
```python
# Create a The odds api Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["the_odds_api"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for The odds api
const session = await composio.create(userId as string, {
  toolkits: ['the_odds_api'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access The odds api. "
        "Help users perform The odds api operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access The odds api. Help users perform The odds api operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["the_odds_api"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access The odds api. "
        "Help users perform The odds api operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['the_odds_api'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access The odds api. Help users perform The odds api operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

This was a starter code for integrating The odds api MCP with OpenAI Agents SDK to build a functional AI agent that can interact with The odds api.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build The odds api MCP Agent with another framework

- [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)

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## 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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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.

---
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