# How to integrate Memberspot MCP with LangChain

```json
{
  "title": "How to integrate Memberspot MCP with LangChain",
  "toolkit": "Memberspot",
  "toolkit_slug": "memberspot",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/memberspot/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/memberspot/framework/langchain.md",
  "updated_at": "2026-05-12T10:18:42.518Z"
}
```

## Introduction

This guide walks you through connecting Memberspot to LangChain using the Composio tool router. By the end, you'll have a working Memberspot agent that can list all users enrolled in a course, find a user by their email address, revoke access to a specific offer for a user through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Memberspot account through Composio's Memberspot MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Memberspot with

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

## TL;DR

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

The Memberspot MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Memberspot account. It provides structured and secure access to your courses, users, and offers, so your agent can perform actions like managing users, automating enrollments, updating offer states, and retrieving key membership data on your behalf.
- User management and lookup: Instantly find users by email, list all users, or remove users from your Memberspot platform without manual searching.
- Automated login token generation: Have your agent generate one-hour login tokens for seamless and secure user access to your courses.
- Offer and enrollment control: Let your agent fetch all available offers, activate or deactivate orders, and manage access to course offers for specific users.
- Custom user property retrieval: Effortlessly list and access all defined custom user properties to enrich learner profiles and personalize experiences.
- Bulk user and order updates: Enable your agent to efficiently update offer states or revoke access for multiple users at once, streamlining membership operations.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `MEMBERSPOT_CREATE_LOGIN_TOKEN` | Create Login Token | Tool to generate a one-hour login token for a user. Use when you need to auto-login a user by their UID (token expires after one hour). |
| `MEMBERSPOT_DELETE_USERS` | Delete Users | Tool to delete one or more users from the platform. Use when you need to remove specified users by their email addresses. Only existing school users are removed; invalid or out-of-school emails are ignored. |
| `MEMBERSPOT_DELETE_USERS_POST` | Delete Users (POST) | Tool to delete multiple users by email using POST method. Use this if your client does not support DELETE with body. Only existing school users are removed; invalid or out-of-school emails are ignored. |
| `MEMBERSPOT_FIND_USER_BY_MAIL` | Find user by email | Tool to retrieve a user's details by their email address. Use when you need to look up a user after obtaining their email. |
| `MEMBERSPOT_GET_USER_COURSE_PROGRESS` | Get user course progress | Tool to retrieve user course progress for a specific course and email. Use when you need to check how far a user has progressed through a particular course. Returns details including active posts, completed posts, and user information. Rate limited to 4 requests per second. |
| `MEMBERSPOT_GRANT_USER_OFFER_BY_MAIL` | Grant user offer by email | Tool to grant a user access to an offer by email. If the user does not exist, a new user is created automatically. |
| `MEMBERSPOT_LIST_CUSTOM_USER_PROPERTIES` | List custom user properties | Tool to list all defined custom user properties. Use when you need to retrieve metadata of custom user properties after authentication. |
| `MEMBERSPOT_LIST_OFFERS` | List all offers | Retrieves all available offers (products/course bundles) from the Memberspot school. Use this to discover offer IDs before granting or revoking user access. Each offer contains course IDs it grants access to and metadata like priority and update time. No parameters required - returns all offers in the school. |
| `MEMBERSPOT_LIST_USER_COURSE_PROGRESS` | List user course progress | Retrieves paginated list of all course progress for a specific user by email. Use to track user progress across all enrolled courses, including active and completed posts. Rate limited to 4 requests per second. |
| `MEMBERSPOT_LIST_USERS` | List Users | List all users in your Memberspot school with optional filtering and pagination. Use this tool to: - Retrieve all users in your membership platform - Filter users by offer access, course enrollment, or active status - Paginate through large user lists using the nextPage token Returns user details including email, name, creation date, progress, and custom properties. Note: API rate limit is 4 requests per second. |
| `MEMBERSPOT_SET_OFFER_EXPIRES` | Set offer expiration | Tool to set or remove the expiration date for an offer for a user. Use when you need to grant time-limited access to an offer or remove time limits from an existing offer. When no value is provided for expiresAt, the offer expiration will be removed. |
| `MEMBERSPOT_SET_ORDER_STATE` | Set order state | Manages order-based offer access for a user in Memberspot. Use this to activate (grant access), deactivate (revoke access), or delete an order-based offer association. Order IDs typically come from payment providers (Stripe, Copecart, Digistore) after a purchase. |
| `MEMBERSPOT_SET_USER_OFFER_STATE` | Set user offer state | Tool to revoke or set the state of a specific offer for a user. Use after confirming whether the user should gain or lose access. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

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

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

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

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

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## Frequently Asked Questions

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

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

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

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

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