How to integrate Neutrino MCP with CrewAI

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Introduction

This guide walks you through connecting Neutrino to CrewAI 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 CrewAI 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 a Composio API key and configure your Neutrino connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Neutrino
  • Build a conversational loop where your agent can execute Neutrino operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Neutrino connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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 crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Neutrino via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Neutrino MCP URL

Create a Composio Tool Router session for Neutrino

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["neutrino"],
)
url = session.mcp.url
What's happening:
  • You create a Neutrino only session through Composio
  • Composio returns an MCP HTTP URL that exposes Neutrino tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Neutrino Assistant",
    goal="Help users interact with Neutrino through natural language commands",
    backstory=(
        "You are an expert assistant with access to Neutrino tools. "
        "You can perform various Neutrino operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Neutrino MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Neutrino operations.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Neutrino related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_neutrino_agent.py

Complete Code

Here's the complete code to get you started with Neutrino and CrewAI:

python
# file: crewai_neutrino_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

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

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Neutrino assistant agent
    toolkit_agent = Agent(
        role="Neutrino Assistant",
        goal="Help users interact with Neutrino through natural language commands",
        backstory=(
            "You are an expert assistant with access to Neutrino tools. "
            "You can perform various Neutrino operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Neutrino operations.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Neutrino related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Neutrino through Composio's Tool Router. The agent can perform Neutrino operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Neutrino MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Neutrino MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Neutrino MCP with Claude Agent SDK

Google ADK

Google ADK

Use Neutrino MCP with Google ADK

LangChain

LangChain

Use Neutrino MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Neutrino MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Neutrino MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Neutrino MCP with LlamaIndex

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 CrewAI?

Yes, you can. CrewAI 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.

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