How to integrate Elevenreader MCP with Autogen

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Introduction

This guide walks you through connecting Elevenreader to AutoGen using the Composio tool router. By the end, you'll have a working Elevenreader agent that can convert a blog post to audio narration, summarize this article and read aloud, generate an audio version of meeting notes through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Elevenreader account through Composio's Elevenreader MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

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 Elevenreader
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Elevenreader tools
  • Run a live chat loop where you ask the agent to perform Elevenreader 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 Elevenreader MCP server, and what's possible with it?

The Elevenreader MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Elevenreader account. It provides structured and secure access so your agent can perform Elevenreader operations on your behalf.

Supported Tools & Triggers

Tools
Add Documentation To Knowledge BaseTool to add documentation to a conversational AI agent's knowledge base.
Add Pronunciation Dictionary From FileTool to add a pronunciation dictionary from a .
Add Pronunciation Dictionary From RulesTool to add a pronunciation dictionary from rules in ElevenLabs.
Add Pronunciation Dictionary RulesTool to add pronunciation rules to an ElevenLabs pronunciation dictionary.
Add Shared VoiceTool to add a shared voice from another user's public library to your own voice library.
Add ToolTool to add a conversational AI tool to ElevenLabs ConvAI.
Calculate Public LLM Expected CostTool to calculate expected LLM usage costs based on prompt length, knowledge base size, and RAG configuration.
Cancel batch callTool to cancel an active batch call operation.
Compute RAG IndexTool to compute RAG index for a knowledge base document.
Create AgentTool to create a conversational AI agent with ElevenLabs.
Create Agent Response TestTool to create an agent response test for testing conversational AI agents.
Create Audio Native ProjectTool to create an Audio Native enabled project on ElevenLabs.
Create Batch CallTool to submit a batch call request to ElevenLabs ConvAI.
Create File DocumentTool to create a file document in the ElevenLabs knowledge base.
Create FolderTool to create a folder in the ElevenLabs knowledge base.
Create Convai Workspace SecretTool to create a Convai workspace secret in ElevenLabs.
Create Text DocumentTool to create a text document in the ElevenLabs knowledge base.
Create URL DocumentTool to create a URL document in the ElevenLabs knowledge base.
Delete AgentTool to permanently delete an agent from ElevenLabs.
Delete Batch CallTool to delete a specific batch call.
Delete Agent Response TestTool to delete an agent response test.
Delete ConversationTool to delete a conversation by its unique ID.
Delete DubbingTool to permanently delete a dubbing project by its ID.
Delete Knowledge Base DocumentTool to permanently delete a document from the knowledge base.
Delete Phone NumberTool to permanently delete a phone number from ElevenLabs ConvAI.
Delete RAG IndexTool to permanently delete a RAG index from a knowledge base document.
Delete Convai Workspace SecretTool to delete a specific Convai workspace secret.
Delete Speech History ItemTool to permanently delete a speech history item by its ID.
Delete ToolTool to permanently delete a conversational AI tool from ElevenLabs.
Delete Transcript By IdTool to permanently delete a speech-to-text transcript by its ID.
Download Speech History ItemsTool to download speech history items from ElevenLabs.
Duplicate AgentTool to duplicate an existing agent.
Edit VoiceTool to edit an existing voice in ElevenLabs.
Edit Voice SettingsTool to edit voice settings for a specific voice in ElevenLabs.
Generate Composition PlanTool to generate a music composition plan using ElevenLabs Music API.
Get agentTool to retrieve complete details for a specific conversational AI agent by ID.
Get Agent Knowledge Base SizeTool to retrieve the size of a conversational AI agent's knowledge base.
Get Agent Shareable LinkTool to get a shareable link for a conversational AI agent.
Calculate Agent LLM Expected CostTool to calculate expected LLM usage costs for a conversational AI agent.
Get Agent Response TestTool to retrieve agent response test details by test ID.
Get Agent Response Tests SummariesTool to retrieve agent response test summaries by test IDs.
Get Agent SummariesTool to retrieve summaries for multiple agents by their IDs.
Get Agent Widget ConfigTool to retrieve the widget configuration for a conversational AI agent.
Get Audio From History ItemTool to retrieve the audio file from a speech history item.
Get Audio Native Project SettingsTool to retrieve audio native project settings from ElevenLabs.
Get Batch Call By IdTool to retrieve a batch call by its ID.
Get conversation historyTool to retrieve complete conversation details including transcript, metadata, and analysis.
Get ConversationsTool to retrieve conversations from ElevenLabs Conversational AI.
Get Conversation Signed LinkTool to get a signed URL for a conversation with an agent.
Get ConvAI dashboard settingsTool to retrieve ConvAI dashboard settings including configured charts.
Get Documentation From Knowledge BaseTool to retrieve a specific document from a conversational AI agent's knowledge base by document ID.
Get Dubbed FileTool to download a dubbed audio or video file from a dubbing project.
Get Dubbing MetadataTool to retrieve metadata for a dubbing project by ID.
Get Dubbed TranscriptTool to retrieve the transcript of a dubbed audio or video file.
Get Dubbing TranscriptsTool to retrieve transcripts from a dubbing project in various formats.
Get Generate Voice ParametersTool to retrieve voice generation parameters from ElevenLabs.
Get Knowledge Base ContentTool to retrieve the text content of a knowledge base document by ID.
Get Knowledge Base Dependent AgentsTool to retrieve the list of conversational AI agents that depend on a specific knowledge base document.
Get Knowledge Base Source File URLTool to retrieve a signed URL for downloading the source file of a document from the knowledge base.
Get Knowledge Base SummariesTool to retrieve summaries for multiple knowledge base documents by their IDs.
Get Library VoicesTool to retrieve shared voices from the ElevenLabs voice library.
Get Live CountTool to retrieve the count of active ongoing conversations.
Get ModelsTool to retrieve available ElevenLabs speech synthesis models.
Get Or Create RAG IndexesTool to compute or retrieve RAG indexes for knowledge base documents in batch.
Get phone numberTool to retrieve details for a specific phone number by ID.
Get Pronunciation DictionariesTool to get a list of pronunciation dictionaries and their metadata.
Get Pronunciation Dictionary MetadataTool to retrieve metadata for a specific pronunciation dictionary by ID.
Get Pronunciation Dictionary Version PLSTool to download a PLS file with pronunciation dictionary version rules.
Get RAG IndexesTool to retrieve RAG indexes for a specific knowledge base document.
Get RAG Index OverviewTool to retrieve an overview of the RAG (Retrieval-Augmented Generation) index.
Get Resource MetadataTool to retrieve metadata and sharing permissions for a workspace resource.
Get ConvAI workspace secretsTool to retrieve ConvAI workspace secrets with pagination support.
Get ConvAI workspace settingsTool to retrieve ConvAI workspace settings including MCP server access, LiveKit stack configuration, RAG retention, and webhook settings.
Get Signed URL (Deprecated)Tool to get a signed URL for an agent conversation.
Get Similar Library VoicesTool to find similar voices from the ElevenLabs library by uploading an audio sample.
Get Single Use TokenTool to create a single-use token for ElevenLabs API.
Get Speech HistoryTool to list generated speech history items from ElevenLabs.
Get speech history item by IDTool to retrieve complete details for a specific speech history item by ID.
Get Test InvocationTool to retrieve test invocation details by invocation ID.
Get toolTool to retrieve complete details for a specific conversational AI tool by ID.
Get Tool Dependent AgentsTool to retrieve the list of conversational AI agents that depend on a specific tool.
Get ConvAI ToolsTool to retrieve ConvAI tools with pagination support.
Get Transcript By IDTool to retrieve a speech-to-text transcript by its unique ID.
Get Characters Usage MetricsTool to retrieve character usage metrics from ElevenLabs.
Get User InfoTool to retrieve information about the authenticated user, including subscription details, character limits, and voice quotas.
Get User Subscription InfoTool to retrieve detailed subscription information for the authenticated user.
Get User Voices V2Tool to retrieve voices using the V2 API from ElevenLabs.
Get Voice by IDTool to retrieve complete details for a specific voice by ID.
Get Voice SettingsTool to retrieve the current settings for a specific voice.
Get Default Voice SettingsTool to retrieve default voice settings for speech synthesis.
Get Workspace Batch CallsTool to get all batch calls for a workspace.
Get Workspace Service AccountsTool to retrieve all service accounts in the workspace.
Handle SIP Trunk Outbound CallTool to initiate an outbound call via SIP trunk using ElevenLabs ConvAI.
Import Phone NumberTool to import a phone number (Twilio or SIP trunk) into ElevenLabs ConvAI.
Isolate Audio StreamTool to isolate vocals/speech from audio files using ElevenLabs Audio Isolation API.
List Agent BranchesTool to list all branches for a specific agent.
List Agent Response TestsTool to list agent response tests from ElevenLabs conversational AI.
List AgentsTool to list conversational AI agents from ElevenLabs.
List DubsTool to list dubbing projects from ElevenLabs.
List Knowledge BasesTool to list knowledge base documents from ElevenLabs.
List MCP ServersTool to list all MCP (Model Context Protocol) server configurations in the workspace.
List Phone NumbersTool to list all phone numbers available in your ElevenLabs ConvAI workspace.
List Test InvocationsTool to list test invocations for a specific conversational AI agent.
List WhatsApp AccountsTool to list all WhatsApp accounts available in your ElevenLabs ConvAI workspace.
List Workspace WebhooksTool to list all webhooks configured in your ElevenLabs workspace.
Bulk Move Knowledge Base EntitiesTool to bulk move documents or folders to a target folder in the knowledge base.
Move Knowledge Base EntityTool to move a document or folder to a target folder in the knowledge base.
Patch Agent SettingsTool to patch (partially update) an agent's settings.
Update Pronunciation DictionaryTool to update a pronunciation dictionary.
Post Agent AvatarTool to upload an avatar image for a conversational AI agent.
Register Twilio CallTool to register a Twilio call with ElevenLabs ConvAI and return TwiML.
Remove Pronunciation Dictionary RulesTool to remove rules from a pronunciation dictionary.
Resubmit TestsTool to resubmit failed or specific tests from a previous test invocation.
Retry batch callTool to retry a failed or cancelled batch call.
Run Agent Test SuiteTool to run tests on a conversational AI agent.
Run Conversation SimulationTool to simulate a conversation between an agent and an AI user.
Simulate Conversation (Stream)Tool to simulate a conversation with an AI agent using a streaming endpoint.
Update Agent Response TestTool to update an existing agent response test in ElevenLabs ConvAI.
Update Audio Native Project ContentTool to update audio-native project content by uploading a new txt or HTML file.
Update ConvAI SettingsTool to update ConvAI workspace settings in ElevenLabs.
Update ConvAI dashboard settingsTool to update ConvAI dashboard settings including chart configurations.
Update DocumentTool to update a document in the ElevenLabs knowledge base.
Update Phone NumberTool to update a phone number's configuration in ElevenLabs ConvAI.
Update Convai Workspace SecretTool to update a Convai workspace secret by ID.
Update ToolTool to update a conversational AI tool configuration.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Elevenreader account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Elevenreader via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

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 Elevenreader connections to use

Import dependencies and create Tool Router session

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 Elevenreader session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["elevenreader"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Elevenreader tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

Configure MCP parameters for Autogen

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")}
)

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

Create the model client and agent

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 Elevenreader assistant agent with MCP tools
    agent = AssistantAgent(
        name="elevenreader_assistant",
        description="An AI assistant that helps with Elevenreader operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Elevenreader tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Elevenreader 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")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Elevenreader 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

Complete Code

Here's the complete code to get you started with Elevenreader and AutoGen:

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 Elevenreader session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["elevenreader"]
    )
    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 Elevenreader assistant agent with MCP tools
        agent = AssistantAgent(
            name="elevenreader_assistant",
            description="An AI assistant that helps with Elevenreader 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 Elevenreader 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 Elevenreader 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 Elevenreader, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Elevenreader MCP Agent with another framework

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LangChain

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Vercel AI SDK

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Use Elevenreader MCP with Vercel AI SDK

Mastra AI

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Use Elevenreader MCP with Mastra AI

LlamaIndex

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Use Elevenreader MCP with LlamaIndex

CrewAI

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Use Elevenreader MCP with CrewAI

Claude Code

Claude Code

Use Elevenreader MCP with Claude Code

Codex

Codex

Use Elevenreader MCP with Codex

FAQ

What are the differences in Tool Router MCP and Elevenreader MCP?

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

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

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

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