# How to integrate Groqcloud MCP with LangChain

```json
{
  "title": "How to integrate Groqcloud MCP with LangChain",
  "toolkit": "Groqcloud",
  "toolkit_slug": "groqcloud",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/groqcloud/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/groqcloud/framework/langchain.md",
  "updated_at": "2026-05-12T10:14:26.189Z"
}
```

## Introduction

This guide walks you through connecting Groqcloud to LangChain using the Composio tool router. By the end, you'll have a working Groqcloud agent that can transcribe this spanish audio file to english, list all available ai models on groqcloud, generate the next chat reply from conversation history through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Groqcloud account through Composio's Groqcloud MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Groqcloud with

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

## TL;DR

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

The Groqcloud MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Groqcloud account. It provides structured and secure access to your deployed AI models and inference services, so your agent can perform actions like running chat completions, translating audio, exploring models, and discovering TTS voices on your behalf.
- Run chat-based completions: Let your agent generate context-aware replies or continue conversations using Groqcloud's high-performance AI models.
- Translate audio to English: Quickly transcribe and translate non-English audio files into accurate English text for downstream processing or review.
- Discover and explore available models: Ask your agent to list all supported AI models, then fetch detailed metadata for any model to inform your workflows.
- Find available TTS voices: Retrieve a curated list of supported text-to-speech voices so your agent can select the best fit for voice synthesis tasks.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GROQCLOUD_CREATE_AUDIO_TRANSCRIPTION` | Create Audio Transcription | Tool to transcribe audio into text in the same language as the audio. Use when you need to convert speech to text while preserving the original language. Supports multiple formats including mp3, mp4, wav, and webm. |
| `GROQCLOUD_CREATE_RESPONSE` | Create Response | Tool to create a model response for the given input. Beta endpoint with simplified interface compared to chat completions. Use when you need a streamlined API for generating model responses. |
| `GROQCLOUD_GROQ_CREATE_AUDIO_TRANSLATION` | Create Audio Translation | Tool to translate an audio file into English text. Use when you have a non-English recording and need an accurate English transcript. Use after confirming the file path. |
| `GROQCLOUD_GROQ_CREATE_CHAT_COMPLETION` | Create Chat Completion | Tool to generate a chat-based completion for a conversation. Use when you have a list of prior messages and need the model's next reply. Response completion text is at choices[0].message.content in the returned envelope. |
| `GROQCLOUD_GROQ_RETRIEVE_MODEL` | Retrieve Model | Tool to retrieve detailed information about a specific model. Use after listing models when you need metadata for a chosen model. Returned metadata may change as models update; do not cache. |
| `GROQCLOUD_LIST_MODELS` | List Models | Tool to list all available models and their metadata. Always call this to retrieve current model IDs rather than using hard-coded or cached identifiers, as deprecated names cause failures in GROQCLOUD_GROQ_RETRIEVE_MODEL and GROQCLOUD_GROQ_CREATE_CHAT_COMPLETION. Returns availability and metadata only — excludes usage stats, latency metrics, and pricing. Response may include many models; filter client-side by provider, family, modality, or context length. Frequent polling combined with high-volume requests risks HTTP 429 rate_limit_exceeded; use backoff and minimize call frequency. |
| `GROQCLOUD_LIST_VOICES` | List TTS Voices | Tool to retrieve available TTS voices for Groq PlayAI models. Use when you need to discover voice options before calling text-to-speech. Note: static list maintained manually; no live endpoint exists. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

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

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

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

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

## Related Toolkits

- [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.
- [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.
- [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.
- [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.
- [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows.
- [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application.
- [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities.
- [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization.
- [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications.
- [Apipie ai](https://composio.dev/toolkits/apipie_ai) - Apipie ai is an AI model aggregator offering a single API for accessing top AI models from multiple providers. It helps developers build cost-efficient, latency-optimized AI solutions without juggling multiple integrations.
- [Astica ai](https://composio.dev/toolkits/astica_ai) - Astica ai provides APIs for computer vision, NLP, and voice synthesis. Integrate advanced AI features into your app with a single API key.
- [Bigml](https://composio.dev/toolkits/bigml) - BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient.
- [Botbaba](https://composio.dev/toolkits/botbaba) - Botbaba is a platform for building, managing, and deploying conversational AI chatbots across messaging channels. It streamlines chatbot automation, making it easier to integrate AI into customer interactions.
- [Botpress](https://composio.dev/toolkits/botpress) - Botpress is an open-source platform for building, deploying, and managing chatbots. It helps teams automate conversations and deliver rich, interactive messaging experiences.
- [Chatbotkit](https://composio.dev/toolkits/chatbotkit) - Chatbotkit is a platform for building and managing AI-powered chatbots using robust APIs and SDKs. It lets you easily add conversational AI to your apps for better user engagement.
- [Cody](https://composio.dev/toolkits/cody) - Cody is an AI assistant built for businesses, trained on your company's knowledge and data. It delivers instant answers and insights, tailored for your team.
- [Context7 MCP](https://composio.dev/toolkits/context7_mcp) - Context7 MCP delivers live, version-specific code docs and examples right from the source. It helps developers and AI agents instantly retrieve authoritative programming info—no more out-of-date docs.
- [Customgpt](https://composio.dev/toolkits/customgpt) - CustomGPT.ai lets you build and deploy chatbots tailored to your own data and business needs. Get precise and context-aware AI conversations without writing code.
- [Datarobot](https://composio.dev/toolkits/datarobot) - Datarobot is a machine learning platform that automates model development, deployment, and monitoring. It empowers organizations to quickly gain predictive insights from large datasets.
- [Deepgram](https://composio.dev/toolkits/deepgram) - Deepgram is an AI-powered speech recognition platform for accurate audio transcription and understanding. It enables fast, scalable speech-to-text with advanced audio intelligence features.

## Frequently Asked Questions

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

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

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

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

---
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