How to integrate Alpha vantage MCP with LangChain

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Introduction

This guide walks you through connecting Alpha vantage to LangChain 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 LangChain 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
  • Connect your Alpha vantage project to Composio
  • Create a Tool Router MCP session for Alpha vantage
  • Initialize an MCP client and retrieve Alpha vantage tools
  • Build a LangChain agent that can interact with Alpha vantage
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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 this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

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
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Alpha vantage functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Alpha vantage tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Alpha vantage
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['alpha_vantage']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Alpha vantage 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
  • This approach allows the agent to dynamically load and use Alpha vantage tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "alpha_vantage-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Alpha vantage MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Alpha vantage tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Alpha vantage related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Alpha vantage and LangChain:

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['alpha_vantage']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "alpha_vantage-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Alpha vantage related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Alpha vantage through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

How to build Alpha vantage MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Alpha vantage MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Alpha vantage MCP with Claude Agent SDK

Google ADK

Google ADK

Use Alpha vantage MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Alpha vantage MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Alpha vantage MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Alpha vantage MCP with LlamaIndex

CrewAI

CrewAI

Use Alpha vantage MCP with CrewAI

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 LangChain?

Yes, you can. LangChain 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.

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