The Odds API MCP Server for LlamaIndex 3 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add The Odds API as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to The Odds API. "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in The Odds API?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About The Odds API MCP Server
Equip your AI agent with real-time sports market intelligence via The Odds API MCP server. This integration provides instant access to live odds from dozens of bookmakers across major sports leagues including NFL, NBA, MLB, EPL, and more. Your agent can list all supported sports, retrieve current market odds for specific regions, and check live or historical scores. Whether you are analyzing market trends, tracking your favorite teams, or building a betting advisor, your agent acts as a dedicated sports data analyst through natural conversation.
LlamaIndex agents combine The Odds API tool responses with indexed documents for comprehensive, grounded answers. Connect 3 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Live Odds Retrieval — Get real-time odds for upcoming games from multiple bookmakers.
- Sports Discovery — List all available sports and leagues supported by the API.
- Score Tracking — Check live and recently completed game scores for various sports.
- Market Comparison — Compare prices across different bookmakers and regions (US, UK, EU, AU).
- Historical Auditing — Summarize and analyze past game results and market movements.
The The Odds API MCP Server exposes 3 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect The Odds API to LlamaIndex via MCP
Follow these steps to integrate the The Odds API MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 3 tools from The Odds API
Why Use LlamaIndex with the The Odds API MCP Server
LlamaIndex provides unique advantages when paired with The Odds API through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine The Odds API tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain The Odds API tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query The Odds API, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what The Odds API tools were called, what data was returned, and how it influenced the final answer
The Odds API + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the The Odds API MCP Server delivers measurable value.
Hybrid search: combine The Odds API real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query The Odds API to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying The Odds API for fresh data
Analytical workflows: chain The Odds API queries with LlamaIndex's data connectors to build multi-source analytical reports
The Odds API MCP Tools for LlamaIndex (3)
These 3 tools become available when you connect The Odds API to LlamaIndex via MCP:
get_odds
Get odds for a specific sport
get_scores
Get live and past scores
list_sports
List all available sports
Example Prompts for The Odds API in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with The Odds API immediately.
"Show me the current odds for the next NFL games."
"Check the live scores for the English Premier League."
"List all sports available on The Odds API."
Troubleshooting The Odds API MCP Server with LlamaIndex
Common issues when connecting The Odds API to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpThe Odds API + LlamaIndex FAQ
Common questions about integrating The Odds API MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect The Odds API with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect The Odds API to LlamaIndex
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.