How to integrate Simplekpi MCP with LangChain

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Introduction

This guide walks you through connecting Simplekpi to LangChain 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 LangChain 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
  • Connect your Simplekpi project to Composio
  • Create a Tool Router MCP session for Simplekpi
  • Initialize an MCP client and retrieve Simplekpi tools
  • Build a LangChain agent that can interact with Simplekpi
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

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

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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 your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Simplekpi functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Simplekpi tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Simplekpi
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['simplekpi']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Simplekpi 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
  • This approach allows the agent to dynamically load and use Simplekpi tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "simplekpi-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Simplekpi MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Simplekpi tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

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

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

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

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['simplekpi']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "simplekpi-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Simplekpi related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

Conclusion

You've successfully built a LangChain agent that can interact with Simplekpi through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

How to build Simplekpi MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

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Claude Agent SDK

Claude Agent SDK

Use Simplekpi MCP with Claude Agent SDK

Google ADK

Google ADK

Use Simplekpi MCP with Google ADK

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 LangChain?

Yes, you can. LangChain 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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