# How to integrate Mezmo MCP with Pydantic AI ```json { "title": "How to integrate Mezmo MCP with Pydantic AI", "toolkit": "Mezmo", "toolkit_slug": "mezmo", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/mezmo/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/mezmo/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:18:55.352Z" } ``` ## Introduction This guide walks you through connecting Mezmo to Pydantic AI using the Composio tool router. By the end, you'll have a working Mezmo agent that can send application error logs to mezmo, delete outdated pipeline alert for a component, ingest security event logs from last hour through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Mezmo account through Composio's Mezmo MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Mezmo with - [OpenAI Agents SDK](https://composio.dev/toolkits/mezmo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/mezmo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/mezmo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/mezmo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/mezmo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/mezmo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/mezmo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/mezmo/framework/cli) - [Google ADK](https://composio.dev/toolkits/mezmo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/mezmo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/mezmo/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/mezmo/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/mezmo/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/mezmo/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 Mezmo - 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 Mezmo 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 Mezmo MCP server, and what's possible with it? The Mezmo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, and more directly to your Mezmo account. It provides structured and secure access to your log management and telemetry pipelines, so your agent can ingest logs, manage pipeline alerts, streamline monitoring, and automate log-driven workflows on your behalf. - Automated log ingestion: Seamlessly send structured log events from any host or service to Mezmo for real-time analysis and monitoring. - Pipeline alert deletion: Direct your agent to remove specific alerts tied to components in your pipelines, helping manage noise and maintain alert hygiene. - Streamlined alert management: Enable your agent to clean up outdated or redundant alerts, keeping your pipeline monitoring focused and actionable. - Real-time telemetry processing: Let your agent push telemetry data instantly for advanced analytics, troubleshooting, and observability workflows. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `MEZMO_CREATE_CATEGORY` | Create Category | Tool to create a new category for views, boards, or screens in Mezmo. Use when organizing Mezmo resources into categories. | | `MEZMO_CREATE_INGESTION_EXCLUSION` | Create Ingestion Exclusion Rule | Tool to create an exclusion rule for log ingestion to control costs. Use this when you need to prevent specific logs from being ingested or stored based on query patterns. Exclusion rules help reduce ingestion costs by filtering out debug logs, test environment logs, or other non-essential log data. | | `MEZMO_CREATE_KEY` | Create API Key | Tool to create a new API key (ingestion or service key) in Mezmo. The API auto-generates a unique name for the key. Use when you need to provision a new key for log ingestion or API access. | | `MEZMO_CREATE_MEMBER` | Create Member Invitation | Tool to invite a new member to the Mezmo organization with a specified role. Use this to send invitations to team members and optionally assign them to specific groups. | | `MEZMO_CREATE_PRESET_ALERT` | Create Preset Alert | Tool to create a new preset alert in Mezmo with specified name and notification channels. Use this to configure alerts that can be triggered based on log conditions. Supports email, PagerDuty, and webhook notification channels. | | `MEZMO_CREATE_VIEW` | Create View | Tool to create a new Mezmo view with filtering and alert configuration. Use when you need to set up custom log views with specific filters (query, hosts, apps, levels, tags) and optional alert channels (email, PagerDuty, webhook). At least one filter parameter must be provided in addition to the view name. | | `MEZMO_DELETE_CATEGORY` | Delete Category | Tool to delete a category by its type and ID. Use when you need to remove a view, board, or screen category from Mezmo configuration. | | `MEZMO_DELETE_INGESTION_EXCLUSION` | Delete Ingestion Exclusion | Tool to remove an ingestion exclusion rule by its ID. Use when you need to delete a specific exclusion rule from Mezmo's ingestion configuration. | | `MEZMO_DELETE_KEY` | Delete API Key | Tool to delete an API key by its unique identifier. Use when you need to remove an ingestion key from Mezmo to revoke access. | | `MEZMO_DELETE_MEMBER` | Delete Organization Member | Tool to remove a member from the organization by their email address. Use when you need to revoke a user's access to the organization. | | `MEZMO_DELETE_PIPELINE_ALERT` | Delete Pipeline Alert | Tool to delete an alert for a specific component within a pipeline. Use after confirming pipeline ID, component kind, component ID, and alert ID. | | `MEZMO_DELETE_PRESET_ALERT` | Delete Preset Alert | Tool to delete a preset alert by its ID. Use after confirming the preset alert ID exists. | | `MEZMO_DELETE_VIEW` | Delete View | Tool to delete a view by its ID. Use when you need to remove a specific view from Mezmo. | | `MEZMO_GET_ALERT` | Get Preset Alert | Tool to retrieve details of a specific preset alert by its ID. Use when you need to view the configuration of an existing alert. | | `MEZMO_GET_CATEGORY` | Get Category | Tool to retrieve a category configuration by its type and ID. Use when you need to fetch details about a specific Mezmo category (view, board, or screen). | | `MEZMO_GET_INDEX_RATE_ALERT` | Get Index Rate Alert Configuration | Tool to retrieve current index rate alert settings for the Mezmo account. Use this to check if index rate alerting is enabled and view configured thresholds and notification channels. | | `MEZMO_GET_INGESTION_EXCLUSION` | Get Ingestion Exclusion Rule | Tool to retrieve an ingestion exclusion rule by its ID. Use when you need to fetch details of a specific exclusion rule. | | `MEZMO_GET_INGESTION_STATUS` | Get Ingestion Status | Tool to get the current ingestion status for the Mezmo account. Use when you need to check whether log ingestion is currently active or paused. | | `MEZMO_GET_KEY` | Get API Key | Tool to retrieve an API key configuration by its ID. Use when you need to fetch details about a specific Mezmo API key. | | `MEZMO_GET_MEMBER` | Get Member | Tool to retrieve member information by their ID. Use when you need to fetch details about a specific member in your Mezmo account. | | `MEZMO_GET_STREAM_CONFIG` | Get Stream Configuration | Tool to retrieve the current event streaming configuration for the Mezmo account. Use when you need to check if streaming is enabled and get streaming settings. Returns error details if streaming is unavailable on the account/plan. | | `MEZMO_GET_VIEW` | Get View Details | Tool to retrieve details of a specific view by its ID. Use when you need to fetch view configuration including name, query, filters, and other attributes. | | `MEZMO_INGEST_LOGS` | Ingest Logs to Mezmo | Ingest log lines into Mezmo Log Analysis. Use this tool to send structured log data from hosts, applications, or services to Mezmo for centralized logging, analysis, and alerting. Logs are sent to the Mezmo ingestion endpoint and will appear in the Mezmo dashboard. | | `MEZMO_LIST_ALERTS` | List Preset Alerts | Tool to list all preset alerts configured for the Mezmo account. Use when you need to retrieve notification rules that trigger based on log patterns. Returns preset alert configurations including their channels (email, PagerDuty, webhook). | | `MEZMO_LIST_KEYS` | List API Keys | Tool to list all API keys and ingestion keys configured for the account. Use when you need to retrieve all keys for viewing or management purposes. | | `MEZMO_LIST_MEMBERS` | List Members | Tool to list all team members in the Mezmo account configuration. Use when you need to retrieve information about all members in the organization. | | `MEZMO_LIST_PIPELINES` | List Telemetry Pipelines | Tool to list all telemetry pipelines configured for the account. Use when you need to view or retrieve information about existing pipelines that manage the flow and transformation of telemetry data. | | `MEZMO_LIST_VIEWS` | List Views | Tool to list all views configured for the account. Views are saved search queries and filters for quick access to specific log data. | | `MEZMO_RESUME_INGESTION` | Resume Log Ingestion | Tool to resume log ingestion for the account after it has been stopped. Use when you need to re-enable log collection after a pause. | | `MEZMO_UPDATE_CATEGORY` | Update Category | Tool to update a category name by its type and ID. Use when you need to rename an existing category in Mezmo. | | `MEZMO_UPDATE_INDEX_RATE_ALERT` | Update Index Rate Alert Configuration | Tool to configure index rate alerting settings including thresholds and notification channels. Use this when you need to set up or modify alerts for unusual log ingestion rates based on absolute line counts or statistical deviations. | | `MEZMO_UPDATE_INGESTION_EXCLUSION` | Update Ingestion Exclusion Rule | Tool to update an existing exclusion rule by its ID. Use when you need to modify the query, active status, indexonly behavior, or title of an existing exclusion rule. At least one field (query, active, indexonly, or title) must be provided for update. | | `MEZMO_UPDATE_KEY` | Update API Key | Tool to update an API key name by its ID. Use when you need to rename an existing Mezmo API key. | | `MEZMO_UPDATE_MEMBER` | Update Member Role and Groups | Tool to update a member's role and group assignments by their email address. Use when you need to change a member's permissions or group memberships. | | `MEZMO_UPDATE_PRESET_ALERT` | Update Preset Alert | Tool to update an existing preset alert by ID. Allows modifying the alert's name and notification channels. Use when you need to change alert configuration after creation. Requires full resource representation with both name and channels. | | `MEZMO_UPDATE_VIEW` | Update Mezmo View | Tool to update an existing Mezmo view by its ID. Use when you need to modify a view's name or search query. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Mezmo MCP server is an implementation of the Model Context Protocol that connects your AI agent to Mezmo. It provides structured and secure access so your agent can perform Mezmo 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 Mezmo - 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 Mezmo - MCPServerStreamableHTTP connects to the Mezmo 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 Mezmo 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 Mezmo composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["mezmo"], ) 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 Mezmo endpoint - The agent uses GPT-5 to interpret user commands and perform Mezmo operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent mezmo_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[mezmo_mcp], instructions=( "You are a Mezmo assistant. Use Mezmo 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 - Mezmo 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 Mezmo.\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 Mezmo composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["mezmo"], ) 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 mezmo_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[mezmo_mcp], instructions=( "You are a Mezmo assistant. Use Mezmo 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 Mezmo.\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 Mezmo through Composio's Tool Router. With this setup, your agent can perform real Mezmo 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 + Mezmo 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 Mezmo MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/mezmo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/mezmo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/mezmo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/mezmo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/mezmo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/mezmo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/mezmo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/mezmo/framework/cli) - [Google ADK](https://composio.dev/toolkits/mezmo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/mezmo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/mezmo/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/mezmo/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/mezmo/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/mezmo/framework/crew-ai) ## Related Toolkits - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure. - [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms. - [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place. - [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences. - [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses. - [Alchemy](https://composio.dev/toolkits/alchemy) - Alchemy is a blockchain development platform offering APIs and tools for Ethereum apps. It simplifies building and scaling Web3 projects with robust infrastructure. - [Algolia](https://composio.dev/toolkits/algolia) - Algolia is a hosted search API that powers lightning-fast, relevant search experiences for web and mobile apps. It helps developers deliver instant, typo-tolerant, and scalable search without complex infrastructure. - [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction. - [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting. - [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache. - [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence. - [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place. - [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines. - [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure. - [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code. - [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows. - [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights. - [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews. - [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease. - [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Mezmo MCP? With a standalone Mezmo MCP server, the agents and LLMs can only access a fixed set of Mezmo tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Mezmo 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 Mezmo tools. ### Can I manage the permissions and scopes for Mezmo while using Tool Router? Yes, absolutely. You can configure which Mezmo 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 Mezmo data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)