How to integrate Sendspark MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Sendspark to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Sendspark agent that can add a new prospect to my latest campaign, list all dynamic video campaigns in workspace, fetch prospect data by email for a campaign, check if the sendspark api is currently online through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Sendspark account through Composio's Sendspark 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 Sendspark
  • Configure an AI agent that can use Sendspark as a tool
  • Run a live chat session where you can ask the agent to perform Sendspark 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 Sendspark MCP server, and what's possible with it?

The Sendspark MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Sendspark account. It provides structured and secure access to your video campaigns and prospect data, so your agent can create campaigns, manage prospects, audit webhooks, and fetch campaign analytics on your behalf.

  • Dynamic campaign creation and management: Instantly launch new dynamic video campaigns or fetch details of existing campaigns in your workspace without manual setup.
  • Prospect automation at scale: Add individual or multiple prospects to video campaigns, retrieve their details by email, and streamline personalized outreach in seconds.
  • Webhook auditing and management: List all configured webhooks or remove outdated ones to keep your integrations secure and up-to-date.
  • Campaign analytics and tracking: Retrieve data and performance metrics for your campaigns and prospects to monitor engagement and optimize results.
  • API health monitoring: Check Sendspark API health status before making calls, ensuring your automations always run smoothly.

Supported Tools & Triggers

Tools
Add Multiple Prospects to Dynamic CampaignTool to add multiple prospects to a dynamic campaign in bulk.
Add Prospect to Dynamic Video CampaignTool to add a prospect to a dynamic video campaign.
API Health StatusTool to check the health status of the sendspark api.
Create Dynamic Video CampaignTool to create a dynamic video campaign.
Delete WebhookTool to delete a specific webhook by its id.
Get Campaign Prospect Data By EmailTool to retrieve prospect data by email within a dynamic campaign.
Get Dynamic Campaign by IDTool to retrieve details of a specific dynamic video campaign.
Get Workspace Prospect Data by EmailTool to retrieve prospect data by email in a dynamic campaign.
List Dynamic Video CampaignsTool to list all dynamic video campaigns in a workspace.
List WebhooksTool to list all configured webhooks.

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 Sendspark 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 Sendspark.

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 Sendspark Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["sendspark"]
)

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 sendspark.
  • The router checks the user's Sendspark connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Sendspark.
  • This approach keeps things lightweight and lets the agent request Sendspark 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 Sendspark. "
        "Help users perform Sendspark 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 Sendspark 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 Sendspark 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 Sendspark.
  • 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 Sendspark 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=["sendspark"]
)
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 Sendspark. "
        "Help users perform Sendspark 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 Sendspark MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Sendspark.

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 Sendspark MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Sendspark MCP with Claude Agent SDK

Google ADK

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Use Sendspark MCP with Google ADK

LangChain

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Use Sendspark MCP with LangChain

Vercel AI SDK

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Use Sendspark MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Sendspark MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Sendspark MCP with LlamaIndex

CrewAI

CrewAI

Use Sendspark MCP with CrewAI

FAQ

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

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

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

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

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