How to integrate Simplekpi MCP with Autogen

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Introduction

This guide walks you through connecting Simplekpi to AutoGen using the Composio tool router. By the end, you'll have a working Simplekpi agent that can show me top performing kpis this month, add a new kpi for sales pipeline, generate a report on marketing metrics through natural language commands.

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

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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Simplekpi
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Simplekpi tools
  • Run a live chat loop where you ask the agent to perform Simplekpi operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Simplekpi MCP server, and what's possible with it?

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

Supported Tools & Triggers

Tools
Add User Group ItemTool to assign a group item to a user in SimpleKPI.
Add User KPITool to assign a KPI to a user in SimpleKPI.
Create Category KPITool to create a new KPI within a category in SimpleKPI.
Create GroupTool to create a new group in SimpleKPI.
Create Group ItemTool to create a new item within a group in SimpleKPI.
Create KPITool to create a new KPI with specified configuration.
Create KPI CategoryTool to create a new KPI category in SimpleKPI.
Create KPI UnitTool to create a new KPI unit in SimpleKPI.
Batch KPI EntriesTool to batch create or update multiple KPI entries at once.
Create UserTool to create a new user account in SimpleKPI.
Delete Category KPITool to delete a KPI from a category.
Delete GroupTool to delete a group by ID.
Delete Group ItemTool to delete a group item by ID.
Delete KPITool to delete a KPI by ID.
Delete KPI CategoryTool to delete a KPI category by its ID.
Delete KPI EntryTool to delete a KPI entry by ID.
Delete KPI UnitTool to delete a KPI unit by its ID.
Delete UserTool to delete a user account by ID.
Delete User Group ItemTool to remove a group item assignment from a user.
Delete User KPITool to remove a KPI assignment from a user.
Get All Data EntriesTool to retrieve processed KPI data entries for reports including calculated KPIs.
Get Category KPITool to retrieve a specific KPI within a category.
Get GroupTool to get a specific group by ID from SimplekPI.
Get Group ItemTool to retrieve a specific group item by ID.
Get KPI by IDTool to retrieve a specific KPI by ID from SimpleKPI.
Get KPI CategoryTool to get a specific KPI category by ID from SimpleKPI.
Get KPI EntryTool to retrieve a specific KPI entry by ID.
Get KPI FrequencyTool to get a specific KPI frequency by ID from SimplekPI.
Get KPI Icon by IDTool to retrieve a specific KPI icon by ID.
Get KPI UnitTool to get a specific KPI unit by ID from SimpleKPI.
Get User by IDTool to retrieve a specific user by ID.
Get User Group ItemTool to get a specific group item assigned to a user.
Get User KPITool to retrieve a specific KPI assigned to a user.
List Category KPIsTool to retrieve all KPIs within a specific category.
List Group ItemsTool to get all items within a group.
List GroupsTool to retrieve all groups from SimpleKPI.
List KPI CategoriesTool to get all KPI categories.
List KPI EntriesTool to get all KPI entries filtered by date range and optional criteria.
List KPI FrequenciesTool to get all KPI frequencies.
List KPI IconsTool to retrieve all KPI icons from SimpleKPI.
List All KPIsTool to retrieve all KPIs from a SimpleKPI account.
List All KPI UnitsTool to retrieve all KPI units from a SimpleKPI account.
List User Group ItemsTool to get all group items assigned to a user.
List User KPIsTool to get all KPIs assigned to a specific user.
Update Category KPITool to update a KPI within a category.
Update GroupTool to update an existing group in SimpleKPI.
Update Group ItemTool to update an existing item in a SimpleKPI group.
Update KPITool to update an existing KPI in SimpleKPI.
Update KPI EntryTool to update an existing KPI entry in SimpleKPI.
Update KPI UnitTool to update an existing KPI unit in SimpleKPI.
Update UserTool to update an existing user account in SimpleKPI.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Simplekpi account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

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.

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Simplekpi via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Simplekpi connections to use

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Simplekpi session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["simplekpi"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Simplekpi tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Simplekpi assistant agent with MCP tools
    agent = AssistantAgent(
        name="simplekpi_assistant",
        description="An AI assistant that helps with Simplekpi operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Simplekpi tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Simplekpi related question or task to the agent.\n")

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Simplekpi tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Simplekpi and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Simplekpi session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["simplekpi"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Simplekpi assistant agent with MCP tools
        agent = AssistantAgent(
            name="simplekpi_assistant",
            description="An AI assistant that helps with Simplekpi operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Simplekpi related question or task to the agent.\n")

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Simplekpi through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Simplekpi, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Simplekpi MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Simplekpi MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Simplekpi MCP with Claude Agent SDK

Google ADK

Google ADK

Use Simplekpi MCP with Google ADK

LangChain

LangChain

Use Simplekpi MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Simplekpi MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Simplekpi MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Simplekpi MCP with LlamaIndex

CrewAI

CrewAI

Use Simplekpi MCP with CrewAI

Claude Code

Claude Code

Use Simplekpi MCP with Claude Code

Codex

Codex

Use Simplekpi MCP with Codex

FAQ

What are the differences in Tool Router MCP and Simplekpi MCP?

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

Can I use Tool Router MCP with Autogen?

Yes, you can. Autogen 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 Simplekpi tools.

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

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

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