How to integrate Instatus MCP with CrewAI

This guide walks you through connecting Instatus to CrewAI using the Composio tool router. By the end, you'll have a working Instatus agent that can list your status pages, create incidents, post updates, schedule maintenance, and manage components through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Instatus account through Composio's Instatus MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Instatus is a status page and incident communication platform for service health, incidents, maintenance, monitors, and subscribers. Use it to keep customers informed during outages, planned work, and live service updates.

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Introduction

This guide walks you through connecting Instatus to CrewAI using the Composio tool router. By the end, you'll have a working Instatus agent that can list your status pages, create incidents, post updates, schedule maintenance, and manage components through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Instatus account through Composio's Instatus MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Instatus with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

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

The Instatus MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Instatus account. It provides structured and secure access to your status pages, components, incidents, maintenance, and service health, so your agent can monitor components, report incidents, publish updates, schedule maintenance, and review service history on your behalf.

  • Status page and service visibility: Have your agent list your status pages, review their components, and check the current health and configuration of a specific service.
  • Incident communication: Let the agent create incidents, review affected components and update history, edit incident details, and publish lifecycle updates as conditions change.
  • Maintenance planning: Direct your agent to schedule or start maintenance, inspect planned and past work, revise schedules and public messages, and post progress updates.
  • Component management: Instruct your agent to create status page components and update their health or presentation when service conditions change.
  • Operational history review: Have your agent list incidents and maintenance events to help your team understand recent disruptions, planned work, and current service status.

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

Step by step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Instatus connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Instatus via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

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")
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 Instatus MCP URL
6

Create a Composio Tool Router session for Instatus

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["instatus"])

url = session.mcp.url
What's happening:
  • You create a Instatus only session through Composio
  • Composio returns an MCP HTTP URL that exposes Instatus tools
7

Initialize the MCP Server

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,
    )
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.
8

Create a CLI Chatloop and define the Crew

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")
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.

Complete Code

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

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=["instatus"],
)
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 Instatus through Composio's Tool Router. The agent can perform Instatus 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
TOOLS

Supported Tools

Every Instatus action and event your agent gets out of the box.

Add Incident Update

Post a public lifecycle update to an Instatus incident and change affected component states.

Add Maintenance Update

Post a public progress update to an Instatus maintenance, optionally changing its lifecycle, timing, and affected component states.

Create Component

Create a component on an Instatus status page.

Create Incident

Create an incident on an Instatus status page with optional affected component states.

Create Maintenance

Schedule or start a maintenance on an Instatus status page.

Get Component

Get the current health and configuration of one component on an Instatus status page.

Get Incident

Get one Instatus incident with its affected components and update history.

Get Maintenance

Get one Instatus maintenance with its schedule, affected components, automation settings, and update history.

List Components

List components and their current health for one Instatus status page, including child components where present.

List Incidents

List incidents for an Instatus status page, optionally including or excluding lifecycle statuses.

List Maintenances

List scheduled and historical maintenances for an Instatus status page.

List Status Pages

List status pages available to the connected Instatus account so an agent can discover page IDs for component, incident, and maintenance operations.

Update Component

Change a component's health or presentation on an Instatus status page.

Update Incident

Edit an existing Instatus incident's name, timing, lifecycle status, affected components, or component states.

Update Maintenance

Fully replace an Instatus maintenance's public message, schedule, lifecycle state, affected components and states, and automation settings.

FRAMEWORKS

How to build Instatus MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Instatus MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Instatus MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Instatus MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Instatus MCP with Claude Cowork

Codex logo

Codex

Use Instatus MCP with Codex

OpenClaw logo

OpenClaw

Use Instatus MCP with OpenClaw

Hermes logo

Hermes

Use Instatus MCP with Hermes

CLI logo

CLI

Use Instatus MCP with CLI

Google ADK logo

Google ADK

Use Instatus MCP with Google ADK

LangChain logo

LangChain

Use Instatus MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Instatus MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Instatus MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Instatus MCP with LlamaIndex

FAQ

Frequently asked questions

With a standalone Instatus MCP server, the agents and LLMs can only access a fixed set of Instatus tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Instatus and many other apps based on the task at hand, all through a single MCP endpoint.

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 Instatus tools.

Yes, absolutely. You can configure which Instatus 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.

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 Instatus data and credentials are handled as safely as possible.

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