How to integrate Mezmo MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Mezmo to the OpenAI Agents SDK 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 By the end, you'll have a working Mezmo agent that can send application error logs to mezmo, delete outdated pipeline alert for a component, ingest security event logs from last hour through natural language commands.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 OpenAI Agents SDK 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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Mezmo
  • Configure an AI agent that can use Mezmo as a tool
  • Run a live chat session where you can ask the agent to perform Mezmo operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the 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  • Streamlined alert management: Enable your agent to clean up outdated or redundant alerts, keeping your pipeline monitoring focused and actionable.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 & Triggers

Tools
Create CategoryTool to create a new category for views, boards, or screens in Mezmo.
Create Ingestion Exclusion RuleTool to create an exclusion rule for log ingestion to control costs.
Create API KeyTool to create a new API key (ingestion or service key) in Mezmo.
Create Member InvitationTool to invite a new member to the Mezmo organization with a specified role.
Create Preset AlertTool to create a new preset alert in Mezmo with specified name and notification channels.
Create ViewTool to create a new Mezmo view with filtering and alert configuration.
Delete CategoryTool to delete a category by its type and ID.
Delete Ingestion ExclusionTool to remove an ingestion exclusion rule by its ID.
Delete API KeyTool to delete an API key by its unique identifier.
Delete Organization MemberTool to remove a member from the organization by their email address.
Delete Pipeline AlertTool to delete an alert for a specific component within a pipeline.
Delete Preset AlertTool to delete a preset alert by its ID.
Delete ViewTool to delete a view by its ID.
Get Preset AlertTool to retrieve details of a specific preset alert by its ID.
Get CategoryTool to retrieve a category configuration by its type and ID.
Get Index Rate Alert ConfigurationTool to retrieve current index rate alert settings for the Mezmo account.
Get Ingestion Exclusion RuleTool to retrieve an ingestion exclusion rule by its ID.
Get Ingestion StatusTool to get the current ingestion status for the Mezmo account.
Get API KeyTool to retrieve an API key configuration by its ID.
Get MemberTool to retrieve member information by their ID.
Get Stream ConfigurationTool to retrieve the current event streaming configuration for the Mezmo account.
Get View DetailsTool to retrieve details of a specific view by its ID.
Ingest Logs to MezmoIngest log lines into Mezmo Log Analysis.
List Preset AlertsTool to list all preset alerts configured for the Mezmo account.
List API KeysTool to list all API keys and ingestion keys configured for the account.
List MembersTool to list all team members in the Mezmo account configuration.
List Telemetry PipelinesTool to list all telemetry pipelines configured for the account.
List ViewsTool to list all views configured for the account.
Resume Log IngestionTool to resume log ingestion for the account after it has been stopped.
Update CategoryTool to update a category name by its type and ID.
Update Index Rate Alert ConfigurationTool to configure index rate alerting settings including thresholds and notification channels.
Update Ingestion Exclusion RuleTool to update an existing exclusion rule by its ID.
Update API KeyTool to update an API key name by its ID.
Update Member Role and GroupsTool to update a member's role and group assignments by their email address.
Update Preset AlertTool to update an existing preset alert by ID.
Update Mezmo ViewTool to update an existing Mezmo view by its ID.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Mezmo project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Mezmo.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Mezmo Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["mezmo"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only mezmo.
  • The router checks the user's Mezmo connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Mezmo.
  • This approach keeps things lightweight and lets the agent request Mezmo tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Mezmo. "
        "Help users perform Mezmo operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Mezmo and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Mezmo operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Mezmo.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Mezmo and OpenAI Agents SDK:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["mezmo"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Mezmo. "
        "Help users perform Mezmo operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Mezmo MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Mezmo.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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FAQ

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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right 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.

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