# How to integrate Remote retrieval MCP with LangChain

```json
{
  "title": "How to integrate Remote retrieval MCP with LangChain",
  "toolkit": "Remote retrieval",
  "toolkit_slug": "remote_retrieval",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/remote_retrieval/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/remote_retrieval/framework/langchain.md",
  "updated_at": "2026-05-12T10:23:41.560Z"
}
```

## Introduction

This guide walks you through connecting Remote retrieval to LangChain using the Composio tool router. By the end, you'll have a working Remote retrieval agent that can show all pending laptop return orders, get company info for acme corp, validate your remote retrieval api key through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Remote retrieval account through Composio's Remote retrieval MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Remote retrieval with

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

## TL;DR

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

The Remote retrieval MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Remote retrieval account. It provides structured and secure access to your company’s equipment logistics, so your agent can perform actions like listing equipment return orders, validating API access, and fetching company details on your behalf.
- Comprehensive order tracking and listing: Ask your agent to retrieve a paginated list of all equipment return orders, with optional filters for status or date to keep tabs on ongoing returns.
- Company information retrieval: Let your agent pull detailed company information instantly, helping with audits, reporting, or support workflows.
- API key validation automation: Have your agent confirm that your API key is valid before performing sensitive actions, ensuring secure and authorized access every time.
- Status-based filtering of return orders: Easily filter and fetch orders by their current status (e.g., pending, completed) to streamline logistics reviews or escalation processes.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `REMOTE_RETRIEVAL_CREATE_ORDER` | Create Order | Tool to create IT asset retrieval orders for remote employees. Use when you need to schedule pickup of laptops, monitors, cell phones, or tablets from employees. Supports both return-to-company and recycle-with-data-destruction workflows. |
| `REMOTE_RETRIEVAL_GET_ALL_ORDERS` | Get All Orders | Tool to retrieve a paginated list of all orders. Use when you need to list orders with optional filters like status or dates. Call after authentication. |
| `REMOTE_RETRIEVAL_GET_COMPANY_DETAILS` | Get Company Details | Tool to retrieve detailed information for a company. Use after confirming a valid company_id. |
| `REMOTE_RETRIEVAL_GET_DEVICE_PRICES` | Get Device Prices | Tool to retrieve real-time pricing data for all supported devices. Use when you need current prices for Laptop, Monitor (17-23 inch), Monitor_27 (24-27 inch), Tablet, or Cell Phone. |
| `REMOTE_RETRIEVAL_GET_ORDER_DETAILS` | Get Order Details | Tool to retrieve specific order details by order ID. Use when you need detailed information about an order including employee info, company info, and shipment status (device_type, send_status, return_status). |
| `REMOTE_RETRIEVAL_LIST_PENDING_ORDERS` | List Pending Orders | Tool to retrieve list of all pending orders. Use when you need to check orders awaiting payment completion. Results are paginated up to 25 per page. |
| `REMOTE_RETRIEVAL_VALIDATE_USER` | RemoteRetrieval: Validate User | Tool to validate the provided API key. Use when you need to confirm the API key's validity. |

## Supported Triggers

None listed.

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

The Remote retrieval MCP server is an implementation of the Model Context Protocol that connects your AI agent to Remote retrieval. It provides structured and secure access so your agent can perform Remote retrieval 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 Remote retrieval 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 Remote retrieval 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 Remote retrieval tools as needed
```python
# Create Tool Router session for Remote retrieval
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['remote_retrieval']
)

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "remote_retrieval-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({
    "remote_retrieval-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 Remote retrieval 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 Remote retrieval 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=['remote_retrieval']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "remote_retrieval-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 Remote retrieval 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: ['remote_retrieval']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "remote_retrieval-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 Remote retrieval 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 Remote retrieval 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 Remote retrieval MCP Agent with another framework

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

## Related Toolkits

- [Ashby](https://composio.dev/toolkits/ashby) - Ashby is an applicant tracking system that handles job postings, candidate management, and hiring analytics.
- [Async interview](https://composio.dev/toolkits/async_interview) - Async interview is an on-demand video interview platform for streamlined hiring. Candidates record responses on their schedule, so employers can review anytime.
- [Bamboohr](https://composio.dev/toolkits/bamboohr) - BambooHR is a cloud-based HR management platform for small and mid-sized businesses. It streamlines employee data, HR workflows, and reporting in one easy interface.
- [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date.
- [Connecteam](https://composio.dev/toolkits/connecteam) - Connecteam is a workforce management platform for deskless teams, streamlining operations, HR, and team communication. It helps businesses save time by automating scheduling, time tracking, and staff engagement tasks.
- [Lever](https://composio.dev/toolkits/lever) - Lever is an applicant tracking system that blends sourcing, CRM, and analytics for recruiting. It helps companies scale hiring with collaborative workflows and actionable insights.
- [Recruitee](https://composio.dev/toolkits/recruitee) - Recruitee is collaborative hiring software that centralizes recruitment tasks for teams. It streamlines sourcing, interviewing, and hiring so you can fill roles faster.
- [Sap successfactors](https://composio.dev/toolkits/sap_successfactors) - Sap successfactors is a cloud-based human capital management suite for HR, payroll, recruiting, and talent management. It helps organizations centralize employee data and streamline the entire employee lifecycle.
- [Talenthr](https://composio.dev/toolkits/talenthr) - TalentHR is an intuitive, all-in-one HR tool for managing employee records, leave, and HR workflows. It streamlines HR operations so businesses can focus on people, not paperwork.
- [Workable](https://composio.dev/toolkits/workable) - Workable is an all-in-one HR software platform that streamlines hiring, employee management, and payroll. It helps teams simplify recruiting, onboarding, and staff operations in one place.
- [Workday](https://composio.dev/toolkits/workday) - Workday is a cloud-based ERP platform for HR, finance, and workforce analytics. It streamlines employee management, payroll, and business operations in a single system.
- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options.
- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide.
- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure.
- [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Remote retrieval MCP?

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

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

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

---
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