# How to integrate Convolo ai MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Convolo ai MCP with OpenAI Agents SDK",
  "toolkit": "Convolo ai",
  "toolkit_slug": "convolo_ai",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/convolo_ai/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/convolo_ai/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:07:36.930Z"
}
```

## Introduction

This guide walks you through connecting Convolo ai to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Convolo ai agent that can create a new sales call character, update character backstory for product launch, list all available ai voices for calls through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Convolo ai account through Composio's Convolo ai MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Convolo ai with

- [Claude Agent SDK](https://composio.dev/toolkits/convolo_ai/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/convolo_ai/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/convolo_ai/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/convolo_ai/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/convolo_ai/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/convolo_ai/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/convolo_ai/framework/cli)
- [Google ADK](https://composio.dev/toolkits/convolo_ai/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/convolo_ai/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/convolo_ai/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/convolo_ai/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/convolo_ai/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/convolo_ai/framework/crew-ai)

## 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 Convolo ai
- Configure an AI agent that can use Convolo ai as a tool
- Run a live chat session where you can ask the agent to perform Convolo ai operations

## What is OpenAI 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 Convolo ai MCP server, and what's possible with it?

The Convolo ai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Convolo ai account. It provides structured and secure access so your agent can perform Convolo ai operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CONVOLO_AI_CREATE_CHARACTER` | Create Character | Tool to create a new character. Use when you have name, voice type, backstory, and optional actions ready. |
| `CONVOLO_AI_EVALUATE_CHARACTER` | Evaluate Character Performance | Evaluates a conversation session across 9 quality dimensions (clarity, courtesy, product knowledge, etc.) using AI analysis. Returns structured ratings and feedback. Prerequisites: - A valid session_id from Get Character Response - A character_id from Create Character - Prompt must include [[conversation_history]] placeholder Note: This API requires Professional Plan or higher access. |
| `CONVOLO_AI_GENERATE_STARTER_CONVERSATION` | Generate Starter Conversation | Generates AI-powered conversation starter suggestions for a character. This tool creates contextually relevant opening lines or follow-up dialogue suggestions that can be used to initiate or continue conversations with AI characters. Perfect for chatbots, virtual assistants, game NPCs, or interactive storytelling applications. Use this when you need: - Opening conversation starters for a new interaction (sessionId="-1") - Follow-up suggestions based on an ongoing conversation (provide existing sessionId) - Multiple conversation options to choose from |
| `CONVOLO_AI_GET_CHARACTER_RESPONSE` | Get Character Response | Tool to generate a response from a ConvAI character based on text or audio input. Use when needing a text or voice reply in an ongoing session. |
| `CONVOLO_AI_LIST_VOICES` | List Voices | Tool to retrieve the list of available voice types. Use when selecting voices before generating speech. |
| `CONVOLO_AI_SET_CORE_AI_SETTINGS` | Set Core AI Settings | Updates the core AI settings (model and/or temperature) for an existing Convai character. Use this action to: - Switch the AI model powering a character (e.g., from GPT-4o to Claude) - Adjust response creativity via temperature parameter (0.0=deterministic, 1.0=creative) - Fine-tune character behavior without recreating the character Prerequisites: Requires a valid charID from a previously created character. At least one of model_group_name or temperature must be specified. |
| `CONVOLO_AI_UPLOAD_KNOWLEDGE_BANK` | Upload Knowledge Bank File | Tool to upload a knowledge bank file. Use when you have a file ready to add to Convolo AI's knowledge bank (Enterprise plan only). |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Convolo ai MCP server is an implementation of the Model Context Protocol that connects your AI agent to Convolo ai. It provides structured and secure access so your agent can perform Convolo ai operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Convolo ai project
- Some knowledge of Python or Typescript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

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 Convolo ai.
```python
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
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
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())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only convolo_ai.
- The router checks the user's Convolo ai connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Convolo ai.
- This approach keeps things lightweight and lets the agent request Convolo ai tools only when needed during the conversation.
```python
# Create a Convolo ai Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["convolo_ai"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Convolo ai
const session = await composio.create(userId as string, {
  toolkits: ['convolo_ai'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Convolo ai. "
        "Help users perform Convolo ai 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",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Convolo ai. Help users perform Convolo ai operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
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())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
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=["convolo_ai"]
)
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 Convolo ai. "
        "Help users perform Convolo ai 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())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['convolo_ai'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Convolo ai. Help users perform Convolo ai operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

This was a starter code for integrating Convolo ai MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Convolo ai.
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 Convolo ai MCP Agent with another framework

- [Claude Agent SDK](https://composio.dev/toolkits/convolo_ai/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/convolo_ai/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/convolo_ai/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/convolo_ai/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/convolo_ai/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/convolo_ai/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/convolo_ai/framework/cli)
- [Google ADK](https://composio.dev/toolkits/convolo_ai/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/convolo_ai/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/convolo_ai/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/convolo_ai/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/convolo_ai/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/convolo_ai/framework/crew-ai)

## Related Toolkits

- [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools.
- [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations.
- [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates.
- [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates.
- [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. It helps businesses automate support and streamline interactions through natural, voice-powered conversations.
- [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code.
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- [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources.
- [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates.
- [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality.
- [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster.
- [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment.
- [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support.
- [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach.
- [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback.
- [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Convolo ai MCP?

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

### Can I manage the permissions and scopes for Convolo ai while using Tool Router?

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)