# How to integrate Gagelist MCP with LangChain

```json
{
  "title": "How to integrate Gagelist MCP with LangChain",
  "toolkit": "Gagelist",
  "toolkit_slug": "gagelist",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/gagelist/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/gagelist/framework/langchain.md",
  "updated_at": "2026-05-12T10:12:28.664Z"
}
```

## Introduction

This guide walks you through connecting Gagelist to LangChain using the Composio tool router. By the end, you'll have a working Gagelist agent that can add a new calibration record for this gage, generate calibration certificate for equipment id 2345, list all gages due for calibration this month through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Gagelist account through Composio's Gagelist MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Gagelist with

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

## TL;DR

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

The Gagelist MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Gagelist account. It provides structured and secure access to your calibration records and asset management workflows, so your agent can perform actions like adding new gages, managing calibration events, generating certificates, and retrieving account information on your behalf.
- Seamless calibration record management: Direct your agent to add, update, or delete calibration records, keeping your asset compliance up-to-date with minimal manual effort.
- Automated gage and manufacturer tracking: Have the agent add new gages or manufacturers to your Gagelist inventory, or remove outdated entries as your equipment changes.
- Instant calibration certificate generation: Let your agent generate official PDF calibration certificates from existing records, streamlining audit and reporting processes.
- Account insights and status checks: Quickly retrieve your account settings or overall status, giving you a real-time view into your calibration program's health.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GAGELIST_ADD_CALIBRATION_RECORD` | Add Calibration Record | Creates a new calibration record in GageList to document equipment calibration results. Use this tool to record calibration activities including test results, dates, technician info, and equipment condition. Can optionally link to an existing gage record via EquipmentRefId, or create a standalone calibration record. Supports detailed test data, attachments, and custom fields. |
| `GAGELIST_ADD_GAGE_RECORD` | Add Gage Record | Tool to add a new gage record. Use after gathering all required gage attributes to create a record. |
| `GAGELIST_ADD_MANUFACTURER` | Add Manufacturer | Creates a new manufacturer record in the GageList calibration management system. A manufacturer represents the company that produces gages and measurement instruments. Use this action when you need to add a new manufacturer to the system for tracking and managing calibration records for their equipment. Returns the unique identifier of the newly created manufacturer record. |
| `GAGELIST_AUTHENTICATE_WITH_GAGELIST` | Authenticate with Gagelist | Tool to obtain a Gagelist API access token. Use when you need to authenticate with Gagelist using client credentials. Returns OAuth2 tokens for subsequent requests. |
| `GAGELIST_DELETE_CALIBRATION_RECORD` | Delete Calibration Record | Deletes a calibration record by its ID. This is a destructive operation that permanently removes the record. Verify the record exists before deletion. |
| `GAGELIST_DELETE_GAGE_RECORD` | Delete Gage Record | Deletes a gage record by its ID. The record must exist in the system to be deleted successfully. This operation is destructive and cannot be undone. |
| `GAGELIST_DELETE_MANUFACTURER` | Delete Manufacturer | Tool to delete a manufacturer by its ID. Use after confirming the manufacturer exists. |
| `GAGELIST_GENERATE_CALIBRATION_CERTIFICATE` | Generate Calibration Certificate | Tool to generate a PDF certificate from a calibration record. Use after ensuring record ID and authentication. |
| `GAGELIST_GET_ACCOUNT_SETTINGS` | Get Account Settings | Tool to get account settings. Use after successful authentication to retrieve user-specific settings. |
| `GAGELIST_GET_ACCOUNT_STATUS` | Get account status | Tool to retrieve account status. Use after authenticating with Gagelist. |
| `GAGELIST_GET_ALL_CALIBRATION_RECORDS` | Get all calibration records | Tool to retrieve a paginated list of calibration records. Use after obtaining a valid access token. |
| `GAGELIST_GET_ALL_GAGE_RECORDS` | Get All Gage Records | Tool to retrieve a paginated list of gage records. Use after confirming the access token. |
| `GAGELIST_GET_ALL_MANUFACTURERS` | Get All Manufacturers | Tool to retrieve a list of all manufacturers. Use after obtaining a valid access token. Returns manufacturer details including ID, name, contact information, and timestamps. |
| `GAGELIST_GET_ATTACHMENT` | Get Attachment | Tool to retrieve an attachment by its ID. Use when you need to download file attachments from the system. |
| `GAGELIST_GET_CUSTOM_FIELDS` | Get Custom Fields | Tool to retrieve custom field definitions. Use when you need to list all custom fields configured for both gage and calibration items after authentication. |
| `GAGELIST_GET_SINGLE_CALIBRATION_RECORD` | Get Single Calibration Record | Tool to retrieve details of a single calibration record. Use when you need a specific record's detailed data. Ensure a valid Bearer token is set. |
| `GAGELIST_GET_SINGLE_GAGE_RECORD` | Get Single Gage Record | Retrieves comprehensive details of a single gage/gauge record from GageList by its unique ID. Returns complete gage information including: serial number, control number, manufacturer details, calibration dates and intervals, measurement specifications (range, tolerance, unit of measure), location, responsible user, test templates, and attached files. Use this after obtaining a valid gage ID from GAGELIST_GET_ALL_GAGE_RECORDS or GAGELIST_ADD_GAGE_RECORD. Example: GetSingleGageRecord(id=123) |
| `GAGELIST_UPDATE_ACCOUNT_SETTINGS` | Update Account Settings | Tool to update account settings. Use after retrieving current settings to apply user preference changes. |
| `GAGELIST_UPDATE_CUSTOM_FIELD_VALUES` | Update Custom Field Values | Tool to update custom field values. Use when you need to set or modify custom field values for a gage or calibration record after authentication. |
| `GAGELIST_UPDATE_MANUFACTURER` | Update Manufacturer | Tool to update a manufacturer by its ID. Use after confirming the manufacturer exists. |
| `GAGELIST_UPLOAD_ATTACHMENT_TO_GAGE_RECORD` | Upload Attachment To Gage Record | Tool to upload an attachment to a gage record. Use when adding files to an existing gage record. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "gagelist-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({
    "gagelist-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 Gagelist 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 Gagelist 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=['gagelist']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "gagelist-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 Gagelist 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: ['gagelist']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "gagelist-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 Gagelist 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 Gagelist 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 Gagelist MCP Agent with another framework

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

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- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives.
- [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions.
- [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.
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- [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes.
- [Canny](https://composio.dev/toolkits/canny) - Canny is a platform for managing customer feedback and feature requests. It helps teams prioritize product decisions based on real user insights.
- [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 Gagelist MCP?

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

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

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

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