# How to integrate Ntfy MCP with Pydantic AI ```json { "title": "How to integrate Ntfy MCP with Pydantic AI", "toolkit": "Ntfy", "toolkit_slug": "ntfy", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/ntfy/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/ntfy/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:43:41.259Z" } ``` ## Introduction This guide walks you through connecting Ntfy to Pydantic AI 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 Pydantic AI 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) - [CrewAI](https://composio.dev/toolkits/ntfy/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up your Composio API key and User ID - How to create a Composio Tool Router session for Ntfy - How to attach an MCP Server to a Pydantic AI agent - How to stream responses and maintain chat history - How to build a simple REPL-style chat interface to test your Ntfy workflows ## What is Pydantic AI? Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications. Key features include: - Type Safety: Built on Pydantic for automatic data validation - MCP Support: Native support for Model Context Protocol servers - Streaming: Built-in support for streaming responses - Async First: Designed for async/await patterns ## 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 with an active API key - Basic familiarity with Python and async programming ### 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 Install the required libraries. What's happening: - composio connects your agent to external SaaS tools like Ntfy - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your agent to Composio's API - USER_ID associates your session with your account for secure tool access - OPENAI_API_KEY to access OpenAI LLMs ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to Ntfy - MCPServerStreamableHTTP connects to the Ntfy MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() ``` ### 5. Create a Tool Router Session What's happening: - We're creating a Tool Router session that gives your agent access to Ntfy tools - The create method takes the user ID and specifies which toolkits should be available - The returned session.mcp.url is the MCP server URL that your agent will use ```python async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Ntfy composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["ntfy"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the Ntfy endpoint - The agent uses GPT-5 to interpret user commands and perform Ntfy operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent ntfy_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[ntfy_mcp], instructions=( "You are a Ntfy assistant. Use Ntfy tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - Ntfy API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```python # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Ntfy.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Ntfy composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["ntfy"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") # Attach the MCP server to a Pydantic AI Agent ntfy_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[ntfy_mcp], instructions=( "You are a Ntfy assistant. Use Ntfy tools to help users " "with their requests. Ask clarifying questions when needed." ), ) # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Ntfy.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You've built a Pydantic AI agent that can interact with Ntfy through Composio's Tool Router. With this setup, your agent can perform real Ntfy actions through natural language. You can extend this further by: - Adding other toolkits like Gmail, HubSpot, or Salesforce - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Ntfy for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## 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) - [CrewAI](https://composio.dev/toolkits/ntfy/framework/crew-ai) ## 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 Pydantic AI? Yes, you can. Pydantic AI 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. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)