# How to integrate Membervault MCP with Autogen

```json
{
  "title": "How to integrate Membervault MCP with Autogen",
  "toolkit": "Membervault",
  "toolkit_slug": "membervault",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/membervault/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/membervault/framework/autogen.md",
  "updated_at": "2026-05-12T10:18:46.388Z"
}
```

## Introduction

This guide walks you through connecting Membervault to AutoGen using the Composio tool router. By the end, you'll have a working Membervault agent that can list all available courses in your account, enroll user john@example.com in marketing 101, delete user with email jane@sample.com through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Membervault account through Composio's Membervault MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Membervault with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Membervault
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Membervault tools
- Run a live chat loop where you ask the agent to perform Membervault operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

## What is the Membervault MCP server, and what's possible with it?

The Membervault MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Membervault account. It provides structured and secure access to your digital products, so your agent can perform actions like enrolling users in courses, retrieving available offerings, and managing user accounts on your behalf.
- Automated course enrollment: Effortlessly add users to specific courses or digital products without manual intervention, streamlining onboarding.
- Instant course catalog retrieval: Let your agent fetch and list all available courses or products in your Membervault account to help you review or present offerings.
- Complete user deletion: Instruct your agent to permanently remove a user—including all associated data, progress, and quiz answers—from your Membervault account.
- Bulk membership management: Use the agent to handle repetitive user enrollment or cleanup tasks efficiently, reducing administrative overhead.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `MEMBERVAULT_ADD_USER` | Add User to Course | Tool to add a user to a specified product. Use when enrolling a user into a course without duplication. |
| `MEMBERVAULT_DELETE_USER` | Delete User | Tool to completely delete a user from the account, including all data, progress, and quiz answers (irreversible). Use when you need to permanently remove a user. Example: "Delete user with email user@example.com" |
| `MEMBERVAULT_GET_COURSES` | Get Courses | Tool to retrieve all courses (products) in the MemberVault account. Use when you need to list available courses after setting up authentication. |
| `MEMBERVAULT_REMOVE_USER` | Remove User from Course | Tool to remove a user's access to a product (course). This simply removes access to the product without deleting the user from the account. Use when revoking course access. |

## Supported Triggers

None listed.

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

The Membervault MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Membervault. Instead of manually wiring Membervault APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Membervault account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Membervault via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Membervault connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Membervault tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Membervault session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["membervault"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Membervault tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Membervault assistant agent with MCP tools
    agent = AssistantAgent(
        name="membervault_assistant",
        description="An AI assistant that helps with Membervault operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Membervault tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Membervault related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Membervault session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["membervault"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Membervault assistant agent with MCP tools
        agent = AssistantAgent(
            name="membervault_assistant",
            description="An AI assistant that helps with Membervault operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Membervault related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

## Conclusion

You now have an Autogen assistant wired into Membervault through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Membervault, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Membervault MCP Agent with another framework

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

## Related Toolkits

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- [Google Classroom](https://composio.dev/toolkits/google_classroom) - Google Classroom is a free web service for educators and students to manage assignments and communication. It streamlines classroom collaboration and grading, making teaching simpler and more connected.
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- [Memberspot](https://composio.dev/toolkits/memberspot) - Memberspot is an online course and video-hosting platform for business learning. It helps teams manage, deliver, and track knowledge efficiently.
- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options.
- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
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- [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide.
- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
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## Frequently Asked Questions

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

With a standalone Membervault MCP server, the agents and LLMs can only access a fixed set of Membervault tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Membervault and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Autogen?

Yes, you can. Autogen 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 Membervault tools.

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

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

---
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