How to integrate Alpha vantage MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Alpha vantage to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Alpha vantage agent that can get latest brent crude oil prices, show upcoming earnings calendar for tech stocks, fetch annual balance sheet for apple, retrieve historical global coffee price data through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Alpha vantage account through Composio's Alpha vantage MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

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 Alpha vantage
  • Configure an AI agent that can use Alpha vantage as a tool
  • Run a live chat session where you can ask the agent to perform Alpha vantage operations

What is open-ai-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 Alpha vantage MCP server, and what's possible with it?

The Alpha Vantage MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Alpha Vantage account. It provides structured and secure access to real-time and historical financial data, so your agent can fetch market prices, analyze commodities, review company financials, and retrieve earnings transcripts on your behalf.

  • Get global commodities and market prices: Instantly retrieve real-time and historical price indices for all major commodities and markets—including aluminum, copper, coffee, corn, and crude oil.
  • Analyze company financial statements: Ask your agent to fetch detailed annual or quarterly balance sheets for any supported company, making fiscal analysis a breeze.
  • Access upcoming earnings calendars: Pull comprehensive earnings schedules for the next three months, so you never miss an important financial event.
  • Retrieve earnings call transcripts with sentiment: Automatically obtain full-text earnings call transcripts for a given company and quarter, including sentiment signals to help you gauge market tone.
  • Perform historical data research: Let your agent gather time series data for commodities and financial indicators, supporting deeper market research and trend analysis.

Supported Tools & Triggers

Tools
Get All Commodities Price IndexTool to retrieve the global price index of all commodities.
ALUMINUMTool to fetch global aluminum prices.
Balance SheetTool to return annual and quarterly balance sheets for a company.
Brent Crude Oil PricesTool to fetch brent crude oil prices.
Global Coffee PriceTool to retrieve the global coffee price series.
COPPERTool to fetch global price of copper in monthly, quarterly, and annual intervals.
CornTool to retrieve global price of corn in monthly, quarterly, and annual intervals.
COTTONTool to retrieve global cotton prices in monthly, quarterly, and annual intervals.
Earnings CalendarTool to return the earnings calendar for the next three months.
Earnings Call TranscriptTool to retrieve the earnings call transcript for a given company and quarter.
FX Daily Time SeriesTool to fetch daily time series (open, high, low, close) for a currency pair.
FX Monthly Time SeriesTool to get monthly time series (open, high, low, close) for a currency pair.
Income StatementTool to fetch annual and quarterly income statements.
IPO CalendarTool to retrieve the ipo calendar for the next three months.
Listing StatusTool to fetch listing status of us stocks and etfs.
News SentimentTool to fetch live and historical market news & sentiment.
Stock SplitsTool to retrieve historical stock split events for a symbol.
Global Sugar PriceTool to retrieve the global sugar price series.
Technical IndicatorTool to fetch technical indicators for the specified equity or currency pair.
WHEATTool to fetch global price of wheat.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Alpha vantage project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

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
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 Alpha vantage.

Set up the Composio instance

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())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Alpha vantage Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["alpha_vantage"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only alpha_vantage.
  • The router checks the user's Alpha vantage connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Alpha vantage.
  • This approach keeps things lightweight and lets the agent request Alpha vantage tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Alpha vantage. "
        "Help users perform Alpha vantage 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",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Alpha vantage and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Alpha vantage operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

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())
What's happening:
  • The program prints a session URL that you visit to authorize Alpha vantage.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Alpha vantage and open-ai-agents-sdk:

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=["alpha_vantage"]
)
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 Alpha vantage. "
        "Help users perform Alpha vantage 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())

Conclusion

This was a starter code for integrating Alpha vantage MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Alpha vantage.

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 Alpha vantage MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Alpha vantage MCP?

With a standalone Alpha vantage MCP server, the agents and LLMs can only access a fixed set of Alpha vantage tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Alpha vantage 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 Alpha vantage tools.

Can I manage the permissions and scopes for Alpha vantage while using Tool Router?

Yes, absolutely. You can configure which Alpha vantage 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 Alpha vantage data and credentials are handled as safely as possible.

Used by agents from

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ASU
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Altera
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Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

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