# How to integrate Optimoroute MCP with LangChain

```json
{
  "title": "How to integrate Optimoroute MCP with LangChain",
  "toolkit": "Optimoroute",
  "toolkit_slug": "optimoroute",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/optimoroute/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/optimoroute/framework/langchain.md",
  "updated_at": "2026-05-12T10:21:00.158Z"
}
```

## Introduction

This guide walks you through connecting Optimoroute to LangChain using the Composio tool router. By the end, you'll have a working Optimoroute agent that can list all active drivers on duty today, show planned delivery routes for tomorrow, find unassigned orders for this week through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Optimoroute account through Composio's Optimoroute MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Optimoroute with

- [OpenAI Agents SDK](https://composio.dev/toolkits/optimoroute/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/optimoroute/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/optimoroute/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/optimoroute/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/optimoroute/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/optimoroute/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/optimoroute/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/optimoroute/framework/cli)
- [Google ADK](https://composio.dev/toolkits/optimoroute/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/optimoroute/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/optimoroute/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/optimoroute/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/optimoroute/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Optimoroute project to Composio
- Create a Tool Router MCP session for Optimoroute
- Initialize an MCP client and retrieve Optimoroute tools
- Build a LangChain agent that can interact with Optimoroute
- 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 Optimoroute MCP server, and what's possible with it?

The Optimoroute MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Optimoroute account. It provides structured and secure access to your logistics and planning data, so your agent can perform actions like retrieving driver details, viewing planned delivery routes, checking route assignments, and monitoring driver status on your behalf.
- Live driver roster and status retrieval: Instantly fetch up-to-date information about all drivers, including their current availability and contact details.
- Planned route overview for any date: Have your agent pull a detailed list of all planned routes for a specific date, including stop information and route parameters.
- Monitor unassigned orders and route gaps: Easily identify orders that haven’t been assigned to a route, helping you spot scheduling bottlenecks.
- Centralized route and driver reporting: Aggregate route and driver data to power dashboards or daily logistics summaries, all via your AI agent.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `OPTIMOROUTE_CREATE_ORDER` | Create Order | Tool to create a new order or update an existing order in OptimoRoute. Use when you need to add delivery, pickup, or task orders to the system with location, time windows, and other constraints. |
| `OPTIMOROUTE_CREATE_OR_UPDATE_ORDERS` | Create or Update Orders | Tool to bulk create, update, or replace multiple orders at once without geocoding. Use when you need to add new orders or modify existing ones efficiently. Supports up to 500 orders per request. |
| `OPTIMOROUTE_DELETE_ALL_ORDERS` | Delete All Orders | Tool to remove all orders and planned routes for a specified date. Use when you need to clear orders for a specific date or delete all orders system-wide if no date is provided. |
| `OPTIMOROUTE_DELETE_ORDER` | Delete Order | Tool to remove a single order from the OptimoRoute system. Use when you need to delete a specific order by its orderNo. |
| `OPTIMOROUTE_DELETE_ORDERS` | Delete Orders | Tool to delete one or more orders from the system in bulk (max 500 per request). Use when you need to remove orders, either individually or in batch operations. |
| `OPTIMOROUTE_GET_COMPLETION_DETAILS` | Get Order Completion Details | Tool to retrieve completion details for one or more orders including proof of delivery data. Use when you need to check order completion status, timing details, and form data. |
| `OPTIMOROUTE_GET_DRIVERS` | Get Drivers | Tool to retrieve all drivers in the system. Use when you need up-to-date driver data including status and contact information. |
| `OPTIMOROUTE_GET_EVENTS` | Get Mobile Events | Tool to retrieve mobile events from drivers' field operations. Use when you need to track order completions, status changes (success, failed, on_duty, off_duty), and other field events for the currently active plan. |
| `OPTIMOROUTE_GET_ORDERS` | Get Orders | Tool to retrieve one or more orders from OptimoRoute. Use when you need detailed order information including location, time windows, and assignment details. |
| `OPTIMOROUTE_GET_PLANNING_STATUS` | Get Planning Status | Tool to retrieve the status of an active planning/optimization process. Use when you need to check the progress of a planning job by providing its ID. |
| `OPTIMOROUTE_GET_ROUTES` | Get Planned Routes | Tool to retrieve all planned routes for a given date. Use when you need a detailed view of routes including optional stops, route parameters, and unassigned orders. |
| `OPTIMOROUTE_GET_SCHEDULING_INFO` | Get Order Scheduling Info | Tool to retrieve scheduling information for a specific order. Use when you need to check if an order is scheduled and get details like driver assignment, timing, and position. |
| `OPTIMOROUTE_SEARCH_ORDERS` | Search Orders | Tool to search for orders in OptimoRoute based on criteria. Use when you need to find orders by date range, order identifiers, or order status. At least one of 'orders' or 'date_range' must be provided. |
| `OPTIMOROUTE_START_PLANNING` | Start Planning | Tool to start the planning/optimization process for a specified date or date range. Use when you need to generate optimized routes for orders and drivers. Requires orders to be created before planning can begin. |
| `OPTIMOROUTE_STOP_PLANNING` | Stop Planning | Tool to stop an active planning/optimization process. Use when you need to halt a running planning job by providing its ID. |
| `OPTIMOROUTE_UPDATE_DRIVER_PARAMETERS` | Update Driver Parameters | Tool to update driver parameters for a specific date including work times, vehicle assignment, and start/end locations. Use when you need to modify driver availability or routing constraints. Note that this unschedules existing routes for the driver on the specified date. |
| `OPTIMOROUTE_UPDATE_DRIVERS_PARAMETERS` | Update Drivers Parameters | Tool to update parameters of multiple drivers for specified dates in bulk (max 500 per request). Use when you need to modify driver configuration including work hours, vehicle assignments, and location settings. Note: Existing routes for the specified drivers and dates will be unscheduled. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Optimoroute MCP server is an implementation of the Model Context Protocol that connects your AI agent to Optimoroute. It provides structured and secure access so your agent can perform Optimoroute 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

No description provided.

### 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

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
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()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

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 Optimoroute tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
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")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Optimoroute 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 Optimoroute tools as needed
```python
# Create Tool Router session for Optimoroute
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['optimoroute']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['optimoroute']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "optimoroute-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)
```

```typescript
const client = new MultiServerMCPClient({
    "optimoroute-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Optimoroute 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")
```

```typescript
let conversationHistory: any[] = [];

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

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
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=['optimoroute']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "optimoroute-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 Optimoroute 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())
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['optimoroute']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "optimoroute-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Optimoroute related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Conclusion

You've successfully built a LangChain agent that can interact with Optimoroute 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 Optimoroute MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/optimoroute/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/optimoroute/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/optimoroute/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/optimoroute/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/optimoroute/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/optimoroute/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/optimoroute/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/optimoroute/framework/cli)
- [Google ADK](https://composio.dev/toolkits/optimoroute/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/optimoroute/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/optimoroute/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/optimoroute/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/optimoroute/framework/crew-ai)

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- [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Optimoroute MCP?

With a standalone Optimoroute MCP server, the agents and LLMs can only access a fixed set of Optimoroute tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Optimoroute 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 Optimoroute tools.

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)