# How to integrate Exist MCP with LangChain

```json
{
  "title": "How to integrate Exist MCP with LangChain",
  "toolkit": "Exist",
  "toolkit_slug": "exist",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/exist/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/exist/framework/langchain.md",
  "updated_at": "2026-05-12T10:10:59.628Z"
}
```

## Introduction

This guide walks you through connecting Exist to LangChain using the Composio tool router. By the end, you'll have a working Exist agent that can show your top positive habits last month, list strongest correlations in your data, summarize your tracked mood this week through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Exist account through Composio's Exist MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Exist with

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

## TL;DR

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

The Exist MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Exist account. It provides structured and secure access to your personal analytics data, so your agent can perform actions like analyzing correlations, retrieving user attributes, exploring supported metrics, and inspecting your profile on your behalf.
- Personal profile access and insights: Instantly retrieve and review your Exist user profile, including preferences and account settings, to keep your agent aware of your context.
- Attribute exploration and discovery: Browse and list all available attribute templates or user attributes, making it easy to understand what metrics you can track, analyze, or visualize.
- Correlation analysis: Ask your agent to fetch and explore recent correlations between tracked attributes—like how weather or sleep might relate to your mood or productivity.
- Custom analytics setup: Let your agent help you discover and understand supported attribute templates before you start tracking or updating new data points.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `EXIST_ACQUIRE_ATTRIBUTE_OWNERSHIP` | Acquire Attribute Ownership | Tool to acquire ownership of attributes for the authenticated user. Allows your service to write data to these attributes. Use when you need to create or take ownership of attributes before writing data. Acquiring a templated attribute the user doesn't have yet will create this attribute and give you ownership. |
| `EXIST_GET_ATTRIBUTES_WITH_VALUES` | Get Attributes With Values | Tool to retrieve attributes with their current values for the authenticated user. Use when you need both attribute metadata and their historical values. Results are limited to your read scopes. |
| `EXIST_GET_ATTRIBUTE_TEMPLATES` | Get Attribute Templates | Tool to retrieve a paged list of supported attribute templates. Use when you need to browse available templates before creating or updating data. |
| `EXIST_GET_AVERAGES` | Get Averages | Tool to retrieve the most recent average values for each tracked attribute, with one set per week. Returns overall weekly averages plus daily breakdowns (Monday-Sunday). Use include_historical flag to retrieve historical average records. |
| `EXIST_GET_CORRELATIONS` | Get Correlations | Retrieve a paginated list of correlations discovered between tracked attributes in the last week. Correlations reveal statistical relationships between different metrics (e.g., sleep duration vs mood). Filter by relationship strength, confidence level (statistical significance), or specific attributes. Returns correlation coefficients, p-values, and human-readable descriptions. |
| `EXIST_GET_INSIGHTS` | Get Insights | Tool to retrieve automatically-generated insights about patterns in tracked data for the authenticated user. Insights are observations about correlations, trends, and anomalies (e.g., "You walked more on days you slept well"). Use when analyzing user behavior patterns or displaying personalized feedback. |
| `EXIST_GET_OWNED_ATTRIBUTES` | Get Owned Attributes | Tool to retrieve attributes owned by your service for the authenticated user. Use when you need to limit data updates to only the attributes your service controls. |
| `EXIST_GET_USER_ATTRIBUTES` | Get User Attributes | Tool to retrieve a paged list of the user's attributes without values. Use when you need metadata on available attributes for filtering or selection. Omitting `groups` and `attributes` filters returns the full attribute catalog; use those filters to narrow results and avoid oversized responses. |
| `EXIST_EXIST_GET_USER_PROFILE` | Get User Profile | Tool to retrieve the authenticated user's profile details and preferences. Use after authentication to inspect account settings and status. OAuth scopes granted during authentication determine which fields are returned; missing fields indicate insufficient scopes. Response includes a timezone field; use it when interpreting any date-based attributes. |
| `EXIST_INCREMENT_ATTRIBUTE_VALUES` | Increment Attribute Values | Tool to increment attribute values by a delta amount rather than setting totals. Use for counters and cumulative data. Does not work with string, scale, or time of day attributes. |
| `EXIST_EXIST_OAUTH2_AUTHORIZE` | Exist OAuth2 Authorize | Constructs an OAuth2 authorization URL for Exist.io. This tool generates the URL that users must visit in their browser to grant permissions to your application. After user consent, Exist redirects back to your redirect_uri with an authorization code that can be exchanged for an access token. This action does not make an API call - it only builds the authorization URL. |
| `EXIST_RELEASE_ATTRIBUTE_OWNERSHIP` | Release Attribute Ownership | Tool to release ownership of attributes for the authenticated user. Use when your service will stop providing data for an attribute or becomes inactive. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

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

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

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

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

## Related Toolkits

- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
- [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.
- [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows.
- [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations.
- [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements.
- [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints.
- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
- [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction.
- [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation.
- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.
- [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses.

## Frequently Asked Questions

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

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

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

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

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