# How to integrate Serveravatar MCP with LangChain

```json
{
  "title": "How to integrate Serveravatar MCP with LangChain",
  "toolkit": "Serveravatar",
  "toolkit_slug": "serveravatar",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/serveravatar/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/serveravatar/framework/langchain.md",
  "updated_at": "2026-03-29T06:49:54.927Z"
}
```

## Introduction

This guide walks you through connecting Serveravatar to LangChain using the Composio tool router. By the end, you'll have a working Serveravatar agent that can list all applications deployed on server 'prod-1', restart the database server named 'backend-db', get status of recent deployments on your servers through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Serveravatar account through Composio's Serveravatar MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Serveravatar with

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

## TL;DR

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

The Serveravatar MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Serveravatar account. It provides structured and secure access so your agent can perform Serveravatar operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SERVERAVATAR_DESTROY_BACKUPS` | Destroy Backups | Tool to delete one or more backups from the cloud storage provider. Use when you need to remove specific backups by their IDs from an organization. |
| `SERVERAVATAR_GET_ORGANIZATION` | Get organization details | Tool to retrieve details of a specific organization by ID. Use when you need to fetch information about an organization. |
| `SERVERAVATAR_LIST_APPLICATIONS` | List Applications | Tool to list applications for a specific organization in ServerAvatar. Use when you need to retrieve all applications associated with an organization ID. |
| `SERVERAVATAR_LIST_BACKUPS` | List Backups | Tool to list all backups in a ServerAvatar organization. Use when you need to retrieve backup information including status, size, and expiration dates. |
| `SERVERAVATAR_LIST_ARCHIVED_BACKUPS` | List Archived Backups | Tool to list archived backups for an organization by type. Use when you need to retrieve archived backups filtered by type (filesystem, database, or application). |
| `SERVERAVATAR_LIST_BACKUPS_FOR_DELETED_SERVERS` | List Backups for Deleted Servers | Tool to get list of deleted servers with available backups. Use when you need to retrieve information about servers that have been deleted but still have backup data in the archive. |
| `SERVERAVATAR_LIST_BACKUP_PRESETS` | List Backup Presets | Tool to retrieve backup preset schedules and retention periods for a server. Use when you need to view available backup scheduling options and retention period configurations. |
| `SERVERAVATAR_LIST_CLOUD_SERVER_PROVIDERS` | List Cloud Server Providers | Tool to list connected cloud server provider accounts for an organization. Use when you need to retrieve all connected provider accounts like DigitalOcean, Vultr, Linode, Hetzner, or AWS Lightsail. |
| `SERVERAVATAR_LIST_CLOUD_STORAGE_PROVIDERS` | List Cloud Storage Providers | Tool to list all configured cloud storage providers for an organization. Use when you need to retrieve available storage provider configurations for backups or file storage. |
| `SERVERAVATAR_LIST_CRONJOBS_PRESETS` | List Cronjobs Presets | Tool to retrieve available cronjob presets for a server. Use when you need to get standard cron expressions for scheduling tasks at various intervals. |
| `SERVERAVATAR_LIST_DATABASES` | List Databases | Tool to list databases for a given organization. Use when you need to retrieve all databases or filter by name. |
| `SERVERAVATAR_LIST_GIT_PROVIDERS` | List Git Providers | Tool to list git providers for a specific organization. Use when you need to retrieve all git providers configured for an organization. |
| `SERVERAVATAR_LIST_ORGANIZATION_MEMBERS` | List Organization Members | Tool to list members of a specific organization in ServerAvatar. Use when you need to retrieve all members associated with an organization ID, including their roles and user details. |
| `SERVERAVATAR_LIST_ORGANIZATIONS` | List Organizations | Tool to list all organizations associated with the authenticated user account. Use when you need to retrieve all organizations the user has access to. |
| `SERVERAVATAR_LIST_SERVERS` | List Servers | Tool to list all servers in an organization with pagination support. Use when you need to retrieve servers for a specific organization. |
| `SERVERAVATAR_LIST_TIMEZONES` | List Timezones | Tool to retrieve the list of available timezones with their UTC offsets. Use when you need to get timezone options for creating or configuring applications. |
| `SERVERAVATAR_LIST_WORDPRESS_LANGUAGES` | List WordPress Languages | Tool to retrieve all available WordPress languages. Use when you need to get the list of supported languages for WordPress installation or configuration. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

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

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

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

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

## Related Toolkits

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- [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction.
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- [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache.
- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

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

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

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

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

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