How to integrate SimpleLocalize MCP with LangChain

This guide walks you through connecting SimpleLocalize to LangChain using the Composio tool router. By the end, you'll have a working SimpleLocalize agent that can list translation keys, create translation keys, export translations, manage tags, and review activity through natural language commands. This guide will help you understand how to give your LangChain agent real control over a SimpleLocalize account through Composio's SimpleLocalize MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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SimpleLocalize is a translation management platform for localization keys, translations, languages, imports, exports, and hosted environments. It helps teams ship multilingual apps faster with clean translation workflows and project-wide language control.

14 Tools

Introduction

This guide walks you through connecting SimpleLocalize to LangChain using the Composio tool router. By the end, you'll have a working SimpleLocalize agent that can list translation keys, create translation keys, export translations, manage tags, and review activity through natural language commands.

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

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

Also integrate SimpleLocalize with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

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

The SimpleLocalize MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your SimpleLocalize account. It provides structured and secure access to your localization projects, so your agent can manage translation keys, update translations, organize tags, export content, and review project activity on your behalf.

  • Translation key management: Have your agent create, find, inspect, or permanently delete translation keys and their associated translations.
  • Translation updates: Instruct your agent to search translations and set text or review status for one or many languages.
  • Project organization: Let the agent create or delete tags and check available languages, tags, and hosting environments before making changes.
  • Translation exports: Direct your agent to review supported file formats and export a current snapshot of your translations in the format you need.
  • Activity review: Have your agent retrieve recent project changes so you can monitor localization work and investigate updates.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

Step by step10 STEPS
1

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
2

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.
3

Install dependencies

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters 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/core is the core agent framework
  • dotenv/config loads environment variables
4

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
5

Import dependencies

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();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with SimpleLocalize functionality through MCP
6

Initialize Composio client

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()
    });
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 SimpleLocalize tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

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

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to SimpleLocalize 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 SimpleLocalize tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "simple_localize-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 });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our SimpleLocalize MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available SimpleLocalize tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any SimpleLocalize 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);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept 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 invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

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

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: ['simple_localize']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "simple_localize-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 SimpleLocalize 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 SimpleLocalize 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.
TOOLS

Supported Tools

Every SimpleLocalize action and event your agent gets out of the box.

Create Tag

Create a project tag for organizing translation keys.

Create Translation Key

Create one translation key and optional metadata in the connected project.

Create Translation Keys

Create up to 100 translation keys and report every rejected entry; valid entries may still be created when others fail.

Delete Tag

Permanently delete one project tag by its exact name.

Delete Translation Key

Permanently delete one translation key, including all translations attached to it, by exact key and namespace.

Export Translations

Create downloadable snapshot URLs for project translations in a selected file format.

Get Project Context

Return the connected project and its current languages, tags, and hosting environments so an agent can choose valid identifiers before managing translations.

Get Translation Key

Return full metadata for one translation key selected by key and namespace.

List Activity

Return a manually selected page of recent project changes for operational visibility.

List File Formats

Return the file formats currently accepted by SimpleLocalize exports, including multi-language, beta, and deprecation metadata.

List Translation Keys

Search translation keys and return one controllable page of provider summary fields.

List Translations

Search translations by key, language, text, review state, or namespace and return one page.

Set Translation

Set the text and optional review state for one existing translation key and language.

Set Translations

Set 1 to 100 translations in one request.

FRAMEWORKS

How to build SimpleLocalize MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use SimpleLocalize MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use SimpleLocalize MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use SimpleLocalize MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use SimpleLocalize MCP with Claude Cowork

Codex logo

Codex

Use SimpleLocalize MCP with Codex

OpenClaw logo

OpenClaw

Use SimpleLocalize MCP with OpenClaw

Hermes logo

Hermes

Use SimpleLocalize MCP with Hermes

CLI logo

CLI

Use SimpleLocalize MCP with CLI

Google ADK logo

Google ADK

Use SimpleLocalize MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use SimpleLocalize MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use SimpleLocalize MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use SimpleLocalize MCP with LlamaIndex

CrewAI logo

CrewAI

Use SimpleLocalize MCP with CrewAI

FAQ

Frequently asked questions

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

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 SimpleLocalize tools.

Yes, absolutely. You can configure which SimpleLocalize 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.

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 SimpleLocalize data and credentials are handled as safely as possible.

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