# How to integrate Fomo MCP with LangChain

```json
{
  "title": "How to integrate Fomo MCP with LangChain",
  "toolkit": "Fomo",
  "toolkit_slug": "fomo",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/fomo/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/fomo/framework/langchain.md",
  "updated_at": "2026-05-12T10:12:02.359Z"
}
```

## Introduction

This guide walks you through connecting Fomo to LangChain using the Composio tool router. By the end, you'll have a working Fomo agent that can show latest fomo events from this week, summarize top fomo notifications today, list recent user actions triggering notifications through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Fomo account through Composio's Fomo MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Fomo with

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

## TL;DR

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

The Fomo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fomo account. It provides structured and secure access to your Fomo event data, so your agent can retrieve notifications, track marketing activity, monitor engagement, and surface real-time insights from your website’s social proof events.
- Fetch recent Fomo events: Instantly retrieve a list of all recent user activity events displayed on your website for analytics or reporting.
- Monitor social proof notifications: Allow your agent to access and summarize the latest notification activity to assess campaign performance.
- Analyze marketing conversion data: Let your agent pull event records to help you understand which actions drive conversions or engagement.
- Track user interactions over time: Easily view trends in visitor activity and notification triggers to inform marketing strategy.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `FOMO_CREATE_FOMO_EVENT` | Create Fomo Event | Tool to create a new social proof event in Fomo. Use when you want to display an animated notification on your website showing recent customer activity. Events are created based on notification templates (event_type_id) and can include customer details, location, and product information. |
| `FOMO_CREATE_FOMO_TEMPLATE` | Create Fomo Template | Tool to create a Template (Event Type) in Fomo. Use when building 3rd party Fomo integrations. Templates define the message structure for notification events and can include markdown formatting, custom images, avatar support, and IP-based location mapping. |
| `FOMO_DELETE_FOMO_EVENT` | Delete Fomo Event | Tool to delete a Fomo event by ID. Permanently removes the notification event from the application. Use when you need to remove a specific event from your Fomo account. |
| `FOMO_GET_FOMO_EVENT` | Get Fomo Event | Tool to retrieve a single event by ID from Fomo. Use when you need to fetch details of a specific notification event using its unique identifier. |
| `FOMO_GET_STATISTICS` | Get Fomo Statistics | Tool to fetch notification impressions, clicks, and conversion data for your Fomo application. Returns analytics statistics within a specified date range. Use when you need to analyze notification performance metrics. |
| `FOMO_LIST_EVENTS` | List Fomo Events | Tool to retrieve all notification events from your Fomo application. Use when you need to list, query, or paginate through events. Supports pagination, sorting, and optional metadata about total event counts. |
| `FOMO_SEARCH_EVENT` | Search Event | Tool to search for a specific Fomo event by external_id or email_address. Use when you need to find a single event using a unique identifier. Returns the full event details if found. |
| `FOMO_UPDATE_APPLICATION` | Update Application Settings | Tool to update Fomo application settings including display configuration, notification behavior, theme, position, and UTM tracking parameters. Use when you need to modify widget appearance, timing, or tracking settings for a Fomo application. |
| `FOMO_UPDATE_EVENT` | Update Fomo Event | Tool to update an existing Fomo event. Changes key-value pairs of an event such as location, name, title, or custom fields. Use when you need to modify event properties after creation. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

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

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

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

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

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## Frequently Asked Questions

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

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

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

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

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