# How to integrate Ntfy MCP with CrewAI

```json
{
  "title": "How to integrate Ntfy MCP with CrewAI",
  "toolkit": "Ntfy",
  "toolkit_slug": "ntfy",
  "framework": "CrewAI",
  "framework_slug": "crew-ai",
  "url": "https://composio.dev/toolkits/ntfy/framework/crew-ai",
  "markdown_url": "https://composio.dev/toolkits/ntfy/framework/crew-ai.md",
  "updated_at": "2026-03-29T06:43:41.259Z"
}
```

## Introduction

This guide walks you through connecting Ntfy to CrewAI using the Composio tool router. By the end, you'll have a working Ntfy agent that can send push notification for build failures, notify me of high-priority alerts, broadcast message to all devices through natural language commands.
This guide will help you understand how to give your CrewAI agent real control over a Ntfy account through Composio's Ntfy MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Ntfy with

- [ChatGPT](https://composio.dev/toolkits/ntfy/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/ntfy/framework/antigravity)
- [OpenAI Agents SDK](https://composio.dev/toolkits/ntfy/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/ntfy/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/ntfy/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/ntfy/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/ntfy/framework/codex)
- [Cursor](https://composio.dev/toolkits/ntfy/framework/cursor)
- [VS Code](https://composio.dev/toolkits/ntfy/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/ntfy/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/ntfy/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/ntfy/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/ntfy/framework/cli)
- [Google ADK](https://composio.dev/toolkits/ntfy/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/ntfy/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/ntfy/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/ntfy/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/ntfy/framework/llama-index)

## TL;DR

Here's what you'll learn:
- Get a Composio API key and configure your Ntfy connection
- Set up CrewAI with an MCP enabled agent
- Create a Tool Router session or standalone MCP server for Ntfy
- Build a conversational loop where your agent can execute Ntfy 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 Ntfy MCP server, and what's possible with it?

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `NTFY_CREATE_ACCOUNT` | Create NTFY Account | Tool to register a new user account on ntfy. Use when you need to create a new user account on the ntfy.sh hosted service. Note: This endpoint is not available on self-hosted instances unless signup is explicitly enabled in the server configuration. |
| `NTFY_CREATE_WEBPUSH_SUBSCRIPTION` | Create Web Push Subscription | Tool to register a web push subscription for browser notifications. Use when you need to enable push notifications from ntfy topics through a browser's native push notification system. |
| `NTFY_DELETE_WEBPUSH_SUBSCRIPTION` | Delete Web Push Subscription | Tool to unregister a web push subscription from the ntfy server. Use when you need to remove browser push notifications for a previously registered endpoint. |
| `NTFY_FETCH_CACHED_MESSAGES` | Fetch Cached Messages | Tool to fetch cached messages from a ntfy topic. Use when you need to retrieve previously sent messages stored on the server. Supports filtering by time (duration or timestamp), message ID, content, title, priority, and tags. Set poll=1 to return immediately after fetching available cached messages. |
| `NTFY_FETCH_LATEST_MESSAGE_FROM_TOPIC` | Fetch Latest Message from Topic | Tool to fetch the most recent message from a topic's cache. Use when you need to retrieve the latest message without subscribing to the topic stream. |
| `NTFY_FETCH_SCHEDULED_MESSAGES` | Fetch Scheduled Messages | Tool to fetch messages scheduled for later delivery from a topic. Use when you need to retrieve messages that are set to be delivered at a future date. The poll=1 and scheduled=1 parameters are automatically set to retrieve cached scheduled messages in a single request. |
| `NTFY_GET_ACCOUNT_INFORMATION` | Get Account Information | Tool to retrieve account data for authenticated user or anonymous user. Use when you need to get account information, limits, statistics, or tier details. |
| `NTFY_GET_SERVER_STATISTICS` | Get Server Statistics | Tool to retrieve server statistics including message counts and publishing rates. Use when you need to monitor ntfy server activity and get metrics about message volume. |
| `NTFY_GET_SERVICE_TIERS` | Get Service Tiers | Tool to list all available ntfy service tiers with their limits and features. Use when you need to retrieve subscription tier information including pricing and usage limits. Requires that payments are enabled on the server. |
| `NTFY_GET_FILE_ATTACHMENT_METADATA` | Get File Attachment Metadata | Tool to get file attachment metadata from a message without downloading the file content. Use when you need to check file size, content type, or verify file existence in the ntfy attachment cache. |
| `NTFY_CHECK_NTFY_SERVICE_HEALTH` | Check NTFY Service Health | Tool to check the health status of the ntfy service. Use when you need to verify if the ntfy service is operational and responding correctly. |
| `NTFY_POLL_MESSAGES_FROM_TOPIC` | Poll Messages from Topic | Tool to poll for messages from an ntfy topic without maintaining a long-standing connection. Use when you need to retrieve cached messages and have the connection close immediately after delivery. The connection ends after reading all available messages matching the criteria. |
| `NTFY_PUBLISH_MESSAGE_AS_JSON_TO_NTFY` | Publish Message as JSON to NTFY | Tool to publish messages as JSON to ntfy. Use when you need to send notifications with all parameters in the request body, especially useful for integrations that cannot add custom headers. |
| `NTFY_PUBLISH_MESSAGE_TO_TOPIC` | Publish Message to Topic | Tool to publish a message to a ntfy topic. Use when you need to send notifications or alerts to a topic. Topics are created dynamically if they don't exist. |
| `NTFY_PUBLISH_MESSAGE_TO_TOPIC_PUT` | Publish Message to Topic (PUT) | Tool to publish a message to a topic using PUT method. Use when you need to send notifications to subscribers of a topic. Supports various options like priority, tags, attachments, and scheduled delivery. |
| `NTFY_PUBLISH_MESSAGE_VIA_GET` | Publish Message via GET | Tool to publish messages to ntfy via GET request with URL parameters. Use when PUT/POST methods are unavailable or for simple webhook integration. Supports all message parameters as query strings. Without parameters, sends 'triggered' as message. |
| `NTFY_SEND_MESSAGE_VIA_WEBHOOK` | Send Message via Webhook | Tool to send messages via webhook endpoint using simple GET request. Use when you need a simple webhook-style integration or for clients with limited HTTP support. |
| `NTFY_SUBSCRIBE_TO_NTFY_TOPIC_WITH_FILTERS` | Subscribe to NTFY Topic with Filters | Tool to subscribe to a ntfy topic with filters based on message fields (id, message, title, priority, tags). Use when you need to retrieve specific messages from a topic using filter criteria. Returns matching messages from the topic as a JSON stream. |
| `NTFY_SUBSCRIBE_TO_TOPIC_JSON_STREAM` | Subscribe to Topic (JSON Stream) | Tool to subscribe to a ntfy topic and receive messages as JSON stream. Use when you need to retrieve cached messages from a topic. The action polls the topic and returns immediately with cached messages. |
| `NTFY_SUBSCRIBE_TO_MULTIPLE_NTFY_TOPICS` | Subscribe to Multiple NTFY Topics | Tool to subscribe to multiple ntfy topics simultaneously using comma-separated topic list. Use when you need to receive messages from multiple topics in a single API call. Returns cached messages when used with poll=true parameter. |
| `NTFY_SUBSCRIBE_TO_TOPIC_RAW_STREAM` | Subscribe to Topic (Raw Stream) | Tool to subscribe to a topic and receive message bodies as raw text stream. Use when you need to retrieve messages without metadata like priority, tags, or titles. Each line in the response contains only the message body. Empty lines represent keepalive messages. In streaming mode, the connection remains open to receive new messages. With poll=1, cached messages are returned and the connection closes. |
| `NTFY_TRIGGER_NTFY_WEBHOOK` | Trigger NTFY Webhook | Tool to trigger a webhook to publish a message to an ntfy topic via simple HTTP GET request. Use when you need to send notifications through webhooks without requiring a POST body. Sends a default 'triggered' message if no custom message is provided. |

## Supported Triggers

None listed.

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

The Ntfy MCP server is an implementation of the Model Context Protocol that connects your AI agent to Ntfy. It provides structured and secure access so your agent can perform Ntfy 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:
- Python 3.9 or higher
- A Composio account and API key
- A Ntfy connection authorized in Composio
- An OpenAI API key for the CrewAI LLM
- Basic familiarity with Python

### 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).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

**What's happening:**
- composio connects your agent to Ntfy via MCP
- crewai provides Agent, Task, Crew, and LLM primitives
- crewai-tools[mcp] includes MCP helpers
- python-dotenv loads environment variables from .env
```bash
pip install composio crewai crewai-tools[mcp] python-dotenv
```

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

**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 Ntfy MCP URL
```python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
```

### 5. Create a Composio Tool Router session for Ntfy

**What's happening:**
- You create a Ntfy only session through Composio
- Composio returns an MCP HTTP URL that exposes Ntfy tools
```python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["ntfy"])

url = session.mcp.url
```

### 6. Initialize the MCP Server

**What's Happening:**
- Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
- MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
- Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
- Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
- Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
```python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
```

### 7. Create a CLI Chatloop and define the Crew

**What's Happening:**
- Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
- Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
- Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
- Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
- Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
- Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.
```python
print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

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

## Complete Code

```python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["ntfy"],
)
url = session.mcp.url

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

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

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

## Conclusion

You now have a CrewAI agent connected to Ntfy through Composio's Tool Router. The agent can perform Ntfy 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 Ntfy MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/ntfy/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/ntfy/framework/antigravity)
- [OpenAI Agents SDK](https://composio.dev/toolkits/ntfy/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/ntfy/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/ntfy/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/ntfy/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/ntfy/framework/codex)
- [Cursor](https://composio.dev/toolkits/ntfy/framework/cursor)
- [VS Code](https://composio.dev/toolkits/ntfy/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/ntfy/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/ntfy/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/ntfy/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/ntfy/framework/cli)
- [Google ADK](https://composio.dev/toolkits/ntfy/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/ntfy/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/ntfy/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/ntfy/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/ntfy/framework/llama-index)

## Related Toolkits

- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Slack](https://composio.dev/toolkits/slack) - Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Gong](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
- [Microsoft teams](https://composio.dev/toolkits/microsoft_teams) - Microsoft Teams is a collaboration platform that combines chat, meetings, and file sharing within Microsoft 365. It keeps distributed teams connected and productive through seamless virtual communication.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Slackbot](https://composio.dev/toolkits/slackbot) - Slackbot is a conversational automation tool for Slack that handles reminders, notifications, and automated responses. It boosts team productivity by streamlining onboarding, answering FAQs, and managing timely alerts—all right inside Slack.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [2chat](https://composio.dev/toolkits/_2chat) - 2chat is an API platform for WhatsApp and multichannel text messaging. It streamlines chat automation, group management, and real-time messaging for developers.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agent mail](https://composio.dev/toolkits/agent_mail) - Agent mail provides AI agents with dedicated email inboxes for sending, receiving, and managing emails. It empowers agents to communicate autonomously with people, services, and other agents—no human intervention needed.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.
- [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. It helps you build flexible automations with complex conditions, schedules, and integrations.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Ntfy MCP?

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

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

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

---
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