How to Use the Twelve Data MCP in LangChain

Q: Can I use Twelve Data's financial data with LangChain for multiple assets?

Absolutely. You can list available stocks using getstocklist, and then loop through them, calling the getquote tool on each one. This lets your agent compare market performance across a whole basket of tickers.

Q: If I want to check historical currency rates using Twelve Data and LangChain, how do I start?

You first use getforexlist to see the available pairs. Once you have a pair, call gettimeseries with that specific pair to pull back the desired date range of exchange rate data.

Build multi-step financial reasoning chains with LangChain and the MCP Server.

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Connect Twelve Data MCP to LangChain

Create your Vinkius account to connect Twelve Data to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Twelve Data with LangChain

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Claude

Perplexity

Run complex market analysis using the MCP Server.

You can chain multiple data calls together. Start by calling `search_symbols` to find a ticker, then pass that result to `get_time_series` to pull historical OHLCV data. Finally, use `get_macd` on the resulting dataset to calculate momentum. This sequence lets your agent build a full investment thesis: finding symbols, gathering data, and applying indicators like `get_rsi` in one logical flow.

Compare multiple assets using LangChain.

Need to compare stocks across different exchanges? First, use `get_stock_list` to gather a set of candidates. Then, iterate over those results and call `get_quote` for each one simultaneously. You can even run this process on crypto pairs by first listing them with `get_crypto_list`. LangChain handles the orchestration, letting your agent compare things like current prices (`get_real_time_price`) and basic fundamentals (`get_company_profile`) side-by-side.

Execute full Forex or Crypto strategies via LangChain.

Forex trading requires quick data access. The `get_forex_list` tool shows you what pairs are available, and then calling `get_exchange_rate` gives the live conversion rate. If you're looking at crypto, you start by using `get_crypto_list` to filter exchanges. This structure lets your agent build a whole strategy: check rates, pull the necessary pairs, and track changes over time using `get_time_series`.

Setup guide

Set up Twelve Data MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Twelve Data tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "twelve-data-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Twelve Data transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Twelve Data MCP in LangChain

You build a chain that calls several indicators in sequence. First, you get historical data using `get_time_series`. Then, the agent can feed those values into `get_macd` and `get_bollinger_bands` to determine if an asset is overbought or oversold.

Absolutely. You can list available stocks using `get_stock_list`, and then loop through them, calling the `get_quote` tool on each one. This lets your agent compare market performance across a whole basket of tickers.

The server handles financial time-series data, including OHLCV candle data, real-time quotes, and various technical indicator values like RSI and MACD. All this structured market data is available for your agent to process.

Yes, the client supports aggregating tools from multiple MCP servers. This means you can combine financial data from Twelve Data with other API sources into one single reasoning pipeline.

You first use `get_forex_list` to see the available pairs. Once you have a pair, call `get_time_series` with that specific pair to pull back the desired date range of exchange rate data.

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