How to integrate Neutrino MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Neutrino to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Neutrino agent that can detect profanity in user-submitted comments, convert 50 usd to eur instantly, geocode address to get latitude and longitude, validate if an email address is deliverable through natural language commands.

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

The Neutrino MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Neutrino account. It provides structured and secure access to Neutrino’s robust suite of APIs, so your agent can validate data, analyze geolocations, assess security risks, convert currencies, and clean content automatically on your behalf.

  • Real-time data validation and analysis: Have your agent validate email addresses, check mobile numbers, and analyze BIN (bank identification numbers) for accuracy and reliability.
  • Geolocation and address intelligence: Ask your agent to geocode addresses to coordinates, or perform reverse geocoding to turn latitude and longitude into real-world locations for smarter workflows.
  • Content safety and cleaning: Let your agent scan text for profanity using the Bad Word Filter or sanitize untrusted HTML to ensure safe, presentable content anywhere it’s needed.
  • Security and risk assessment: Automate reputation checks on hosts and domains, enabling your agent to proactively identify potential threats or block risky sources without manual effort.
  • Currency and unit conversion: Empower your agent to convert between different units or currencies on demand, streamlining financial or scientific operations with ease.

Supported Tools & Triggers

Tools
Bad Word FilterTool to detect bad words and profanity in text.
BIN LookupTool to perform a bin (bank iin) lookup.
Convert ValueTool to perform unit and currency conversions.
Validate and analyze an email addressTool to parse, validate, and clean an email address.
Verify Email AddressTool to verify and analyze the deliverability of an email address.
Geocode AddressTool to geocode an address.
Reverse GeocodeTool to convert geographic coordinates to a physical address.
HLR LookupTool to perform real-time hlr lookup and mobile number validation.
Host ReputationTool to check the reputation of a host against dnsbls.
HTML CleanTool to clean and sanitize untrusted html.
HTML RenderTool to render html content into png or pdf.
Resize ImageTool to resize, crop, and convert images.
IP InfoTool to retrieve ip location and network information.
IP LookupTool to geolocate an ip address and retrieve isp, asn, blocklist, and threat metadata.
IP ProbeTool to analyze an ip address to determine its threat level and associated risk factors.
Phone ValidateTool to validate and lookup phone numbers.
QR CodeTool to generate a qr code image from text or url.
SMS VerifyTool to send a unique security code via sms.
UA LookupTool to parse, validate, and get detailed user-agent information.
URL InfoTool to parse, analyze, and retrieve content from the supplied url.
Verify Security CodeTool to verify a security code generated by the generate security code api.

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 Neutrino 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 Neutrino.

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 Neutrino Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["neutrino"]
)

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

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 Neutrino MCP Agent with another framework

FAQ

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

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

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

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

Used by agents from

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Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

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