How to integrate Spondyr MCP with LangChain

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Introduction

This guide walks you through connecting Spondyr to LangChain using the Composio tool router. By the end, you'll have a working Spondyr agent that can list all transaction types in spondyr, create condition rules for refund events, update event type name for shipped orders, get recipient details for invoice delivery through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Spondyr account through Composio's Spondyr 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 Spondyr project to Composio
  • Create a Tool Router MCP session for Spondyr
  • Initialize an MCP client and retrieve Spondyr tools
  • Build a LangChain agent that can interact with Spondyr
  • 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 Spondyr MCP server, and what's possible with it?

The Spondyr MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Spondyr account. It provides structured and secure access to your Spondyr templates, transaction types, events, and correspondence workflows, so your agent can perform actions like managing conditions, handling recipients, orchestrating correspondence delivery, and monitoring status updates for your business communications.

  • Comprehensive transaction type management: Quickly create, list, or update transaction types—making it easy for your agent to adapt Spondyr to your evolving business data needs.
  • Rule-based template selection: Define and manage conditions that control which templates are used for different transaction scenarios, ensuring your communications are always personalized and relevant.
  • Automated correspondence delivery and tracking: Have your agent trigger the delivery of generated correspondence and fetch real-time status updates, so you always know when and how your messages are sent.
  • Dynamic event and recipient handling: List, retrieve, update, or delete event types and recipient information to keep your communication flows flexible and up-to-date.
  • Seamless integration and configuration management: Effortlessly connect, configure, and synchronize your Spondyr settings and workflows—without manual intervention or custom code.

Supported Tools & Triggers

Tools
List ConditionsTool to list all conditions for a transaction type.
Create ConditionTool to create a new condition.
Create Transaction TypeTool to create a new transaction type.
Deliver Spondyr correspondenceTool to trigger delivery of a previously generated correspondence.
Update Event TypeTool to update an existing event type.
List Event TypesTool to list all event types for a given transaction type.
Get Spondyr StatusTool to retrieve the status of a previously generated correspondence.
Get Transaction TypesTool to retrieve a list of available transaction types.
Delete RecipientTool to delete or deactivate a specific recipient.
Get RecipientTool to retrieve details of a specific recipient.
List RecipientsTool to list all recipients for a transaction type.
Create Search FilterTool to create a new search filter.
Delete Search FilterTool to delete or deactivate a specific search filter.
Get Search FilterTool to retrieve details of a specific search filter.
List Search FiltersTool to list all search filters for a transaction type.
Search CorrespondenceTool to search generated correspondence by multiple criteria.
Create Spondyr SSO stubTool to create a one-time sso user stub in spondyr.
Get TemplateTool to retrieve a specific template’s configuration and content reference.
List TemplatesTool to list all templates for a transaction type.
Get Transaction TypeTool to retrieve details of a specific transaction type.
Update Transaction TypeTool to update an existing transaction type.

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 Spondyr 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 Spondyr tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Spondyr 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 Spondyr tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "spondyr-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 Spondyr MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Spondyr 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 Spondyr 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 Spondyr 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=['spondyr']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "spondyr-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 Spondyr 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 Spondyr 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 Spondyr MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Spondyr MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Spondyr MCP with Claude Agent SDK

Google ADK

Google ADK

Use Spondyr MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Spondyr MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Spondyr MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Spondyr MCP with LlamaIndex

CrewAI

CrewAI

Use Spondyr MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Spondyr MCP?

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

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

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

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