How to integrate Elevenreader MCP with LlamaIndex

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Introduction

This guide walks you through connecting Elevenreader to LlamaIndex 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 LlamaIndex 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:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Elevenreader
  • Connect LlamaIndex to the Elevenreader MCP server
  • Build a Elevenreader-powered agent using LlamaIndex
  • Interact with Elevenreader through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

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

Before you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Elevenreader account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Elevenreader

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Elevenreader access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called elevenreader_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["elevenreader"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Elevenreader actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Elevenreader actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, elevenreader)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Elevenreader tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Elevenreader database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Elevenreader

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Elevenreader, then start asking questions.

Complete Code

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

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["elevenreader"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Elevenreader actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Elevenreader actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Elevenreader to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Elevenreader tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

How to build Elevenreader MCP Agent with another framework

OpenAI Agents SDK

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Claude Agent SDK

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Use Elevenreader MCP with Claude Agent SDK

Google ADK

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LangChain

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Use Elevenreader MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Elevenreader MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Elevenreader MCP with Mastra AI

CrewAI

CrewAI

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 LlamaIndex?

Yes, you can. LlamaIndex 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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