# How to integrate Passcreator MCP with LangChain

```json
{
  "title": "How to integrate Passcreator MCP with LangChain",
  "toolkit": "Passcreator",
  "toolkit_slug": "passcreator",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/passcreator/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/passcreator/framework/langchain.md",
  "updated_at": "2026-05-12T10:21:28.144Z"
}
```

## Introduction

This guide walks you through connecting Passcreator to LangChain using the Composio tool router. By the end, you'll have a working Passcreator agent that can find all event tickets created this week, check if a membership card exists for john doe, list available coupon pass templates for your account through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Passcreator account through Composio's Passcreator MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Passcreator with

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

## TL;DR

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

The Passcreator MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Passcreator account. It provides structured and secure access to your digital wallet passes, so your agent can perform actions like searching passes, verifying pass existence, and retrieving pass templates on your behalf.
- Search and filter wallet passes: Quickly ask your agent to locate passes in your account using filters such as external ID, type, or status.
- Verify pass existence: Have your agent check if a specific digital pass already exists before sending updates or making changes.
- Retrieve pass templates: Let your agent list and browse available pass templates for creating or managing new digital passes.
- Support for bulk and paginated operations: Enable your agent to efficiently handle large numbers of passes or templates by using pagination and advanced search.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PASSCREATOR_CHECK_PASS_EXISTENCE` | Check Pass Existence | Tool to check if a pass exists for a given ID. Use when verifying pass existence before subsequent operations like updates or deletions. The ID can be a generatedId (unique ID created for every pass, usually encoded in the barcode), userProvidedId (optional custom ID), or any other identifier associated with a pass. |
| `PASSCREATOR_CREATE_APP_SCAN` | Create App Scan | Tool to create a new App Scan in PassCreator. Use when recording pass validation or attendance scanning events. Supports tracking scan status, device information, and optional pass voiding. |
| `PASSCREATOR_GET_APP_CONFIGURATION` | Get App Configuration | Retrieves detailed information about an App Configuration by its identifier. Use when you need to get scan settings, UI customization, or validation rules for a specific App Configuration. |
| `PASSCREATOR_GET_PROCESS_STATUS` | Get Process Status | Get the current status and progress of a bulk operation including any errors. Use this to monitor long-running bulk operations like batch pass updates or creations. The identifier is returned when initiating a bulk operation. |
| `PASSCREATOR_GET_SIGNING_PUBLIC_KEY` | Get Signing Public Key | Tool to obtain the public key needed to verify signatures from the placeholder sign() function. Use when you need to verify cryptographic signatures generated by Passcreator's sign placeholder. |
| `PASSCREATOR_LIST_APP_CONFIGURATIONS` | List App Configurations | Retrieves all App Configurations for your Passcreator account. Use this action to get a list of validation configurations that control how passes are scanned and validated. Each configuration can be linked to specific pass templates or validate all passes. |
| `PASSCREATOR_LIST_APP_SCANS` | List App Scans | Retrieves a paginated list of scans for a given app configuration. Use this tool to view scan history, track attendance, and analyze scan data ordered by creation date. |
| `PASSCREATOR_LIST_PASSES` | List/Search Passes | List and search wallet passes from Passcreator using the v3 API. Use this tool to: - Retrieve all passes in your account - Filter passes by template ID or project ID - Search passes using a search phrase across all data fields - Paginate through large result sets Returns passes with metadata including identifiers, serial numbers, template info, and voided/redeemed status. |
| `PASSCREATOR_LIST_PASS_TEMPLATES` | List Pass Templates | Retrieves all pass templates for your Passcreator account. Use this action to get a list of available templates (each with its unique identifier and name) which are needed to create new passes. Templates must be created via the Passcreator web app. |
| `PASSCREATOR_SEND_BULK_PUSH_NOTIFICATIONS` | Send Bulk Push Notifications | Tool to send push notifications to multiple wallet passes simultaneously (up to 500 passes). Use when you need to notify pass holders about updates, events, or important information. The notification text can include personalization placeholders like {Firstname}. |
| `PASSCREATOR_UPDATE_PASSES_BULK` | Bulk Update Passes | Tool to bulk update multiple wallet passes using filter criteria. Returns immediately with a tracking URL to monitor the asynchronous bulk operation progress. Use when updating many passes at once with the same data changes. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

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

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

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

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

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## Frequently Asked Questions

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

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

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

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

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