How to integrate Spondyr MCP with Autogen

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Introduction

This guide walks you through connecting Spondyr to AutoGen 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 through natural language commands.

This guide will help you understand how to give your AutoGen 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.

Also integrate Spondyr with

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Spondyr
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Spondyr tools
  • Run a live chat loop where you ask the agent to perform Spondyr operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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 ConditionCreate a condition rule for template selection in Spondyr.
Create Transaction TypeTool to create a new transaction type.
Deliver Spondyr correspondenceTrigger delivery of previously generated correspondence to recipients.
Update Event TypeTool to update an existing event type name within a transaction type.
List Event Types for Transaction TypeRetrieves all event types associated with a specific transaction type in Spondyr.
Get Spondyr StatusTool to retrieve the status of a previously generated correspondence.
Get Transaction TypesTool to retrieve a list of available transaction types.
Delete RecipientDeletes a recipient configuration from a transaction type in Spondyr.
Get RecipientTool to retrieve details of a specific recipient.
List RecipientsTool to list all recipients for a transaction type.
Create Search FilterCreate a new search filter for a transaction type in Spondyr.
Delete Search FilterDeletes a specific search filter from the Spondyr system.
Get Search FilterRetrieves details of a specific search filter in Spondyr by name and transaction type.
List Search FiltersTool to list all search filters for a transaction type.
Search CorrespondenceSearch for generated correspondence (spondyrs) by multiple criteria including batch ID, event type, and custom search filters.
Create Spondyr SSO stubTool to create a one-time SSO user stub in Spondyr.
Get TemplateRetrieve detailed configuration for a specific correspondence template.
List TemplatesList all templates configured for a transaction type.
Get Transaction TypeTool to retrieve details of a specific transaction type.
Update Transaction TypeUpdates an existing transaction type's name and/or JSON schema in Spondyr.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Spondyr account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

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

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Spondyr via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Spondyr connections to use

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Spondyr session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["spondyr"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Spondyr tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Spondyr assistant agent with MCP tools
    agent = AssistantAgent(
        name="spondyr_assistant",
        description="An AI assistant that helps with Spondyr operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Spondyr tools from the workbench

Run the interactive chat loop

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

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Spondyr tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Spondyr and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Spondyr session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["spondyr"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Spondyr assistant agent with MCP tools
        agent = AssistantAgent(
            name="spondyr_assistant",
            description="An AI assistant that helps with Spondyr operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

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

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Spondyr through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Spondyr, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

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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 Autogen?

Yes, you can. Autogen 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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