# How to integrate Callerapi MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Callerapi MCP with OpenAI Agents SDK",
  "toolkit": "Callerapi",
  "toolkit_slug": "callerapi",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/callerapi/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/callerapi/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:04:49.906Z"
}
```

## Introduction

This guide walks you through connecting Callerapi to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Callerapi agent that can check if this phone number is flagged as spam, retrieve carrier and business info for a caller, show your callerapi credit usage this month through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Callerapi account through Composio's Callerapi MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Callerapi with

- [Claude Agent SDK](https://composio.dev/toolkits/callerapi/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/callerapi/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/callerapi/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/callerapi/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/callerapi/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/callerapi/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/callerapi/framework/cli)
- [Google ADK](https://composio.dev/toolkits/callerapi/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/callerapi/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/callerapi/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/callerapi/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/callerapi/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/callerapi/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 Callerapi
- Configure an AI agent that can use Callerapi as a tool
- Run a live chat session where you can ask the agent to perform Callerapi 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 Callerapi MCP server, and what's possible with it?

The Callerapi MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Callerapi account. It provides structured and secure access to caller identification and reputation data, so your agent can perform actions like verifying phone numbers, checking caller reputation, retrieving business and carrier details, and monitoring account usage on your behalf.
- Detailed phone number lookup: Instantly retrieve information about any phone number, including reputation, business association, carrier, and FTC complaints.
- Reputation and fraud assessment: Empower your agent to check if a phone number might be flagged for spam, robocalls, or fraud, helping you screen and validate callers.
- Business and carrier identification: Have your agent fetch in-depth business and carrier details for a given number to strengthen trust and context in communications.
- HLR (Home Location Register) checks: Enable your agent to request HLR data for deeper carrier and number status insights, including ported or roaming status.
- Account usage monitoring: Let your agent access your Callerapi user profile to monitor credit usage, monthly allocations, and remaining balance, keeping you informed about your API consumption.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CALLERAPI_DISPATCH_REPORTS_MANUALLY` | Dispatch Reports Manually | Tool to manually trigger today's spam reports webhook delivery for enterprise clients. Use when an immediate webhook dispatch of spam complaint reports is needed. This endpoint is restricted to enterprise accounts only. |
| `CALLERAPI_GET_PHONE_NUMBER_INFORMATION` | Get Phone Number Information | Tool to retrieve detailed information about a specific phone number, including reputation, business and carrier details, and FTC complaints. Use when the number is in E.164 format and set hlr=true to include HLR data (adds 1-3 seconds to response). |
| `CALLERAPI_GET_USER_INFORMATION` | Get User Information | Tool to retrieve information about the authenticated user, including email and credit usage details. Use after authentication to fetch current credits spent, monthly allocation, and credits left. |
| `CALLERAPI_LIST_WEBHOOK_SUBSCRIPTIONS` | List Webhook Subscriptions | Tool to list all webhook subscriptions for daily spam reports. Enterprise clients only. Use to retrieve all configured webhook endpoints that receive spam complaint notifications. |
| `CALLERAPI_SUBSCRIBE_DAILY_REPORTS` | Subscribe to Daily Spam Reports | Tool to subscribe to daily spam report webhooks for enterprise clients. Instead of polling, receive webhook deliveries with spam complaint data daily. Use when you want to set up automated daily reports for spam complaints. |
| `CALLERAPI_TEST_WEBHOOK` | Test Webhook | Tool to send a sample webhook payload to test your webhook endpoint integration. Use to validate webhook signature verification and endpoint configuration. Enterprise clients only. |
| `CALLERAPI_UNSUBSCRIBE_DAILY_REPORTS` | Unsubscribe from Daily Reports | Tool to unsubscribe from daily spam report webhooks. Use when you need to stop receiving daily reports at a specific webhook URL. Enterprise clients only. |

## Supported Triggers

None listed.

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

The Callerapi MCP server is an implementation of the Model Context Protocol that connects your AI agent to Callerapi. It provides structured and secure access so your agent can perform Callerapi 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 Callerapi 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 Callerapi.
```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 callerapi.
- The router checks the user's Callerapi connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Callerapi.
- This approach keeps things lightweight and lets the agent request Callerapi tools only when needed during the conversation.
```python
# Create a Callerapi Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["callerapi"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Callerapi
const session = await composio.create(userId as string, {
  toolkits: ['callerapi'],
});
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 Callerapi. "
        "Help users perform Callerapi 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 Callerapi. Help users perform Callerapi 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=["callerapi"]
)
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 Callerapi. "
        "Help users perform Callerapi 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: ['callerapi'],
  });
  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 Callerapi. Help users perform Callerapi 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 Callerapi MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Callerapi.
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 Callerapi MCP Agent with another framework

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

## Related Toolkits

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- [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.
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- [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.
- [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows.
- [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 Callerapi MCP?

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

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

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

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