How to integrate Elevenreader MCP with Vercel AI SDK v6

This guide walks you through connecting Elevenreader to Vercel AI SDK v6 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 Vercel AI SDK 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.

Get started for freeGet a demo
Elevenreader logoElevenreader
Api Key

Elevenreader is an AI-powered text-to-speech service by ElevenLabs that converts written content into lifelike audio. It enables fast, natural audio generation from any text.

125 Tools

Introduction

This guide walks you through connecting Elevenreader to Vercel AI SDK v6 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 Vercel AI SDK 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.

Also integrate Elevenreader with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up and configure a Vercel AI SDK agent with Elevenreader integration
  • Using Composio's Tool Router to dynamically load and access Elevenreader tools
  • Creating an MCP client connection using HTTP transport
  • Building an interactive CLI chat interface with conversation history management
  • Handling tool calls and results within the Vercel AI SDK framework

What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.

Key features include:

  • streamText: Core function for streaming responses with real-time tool support
  • MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
  • Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
  • OpenAI Provider: Native integration with OpenAI models

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.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

Step by step09 STEPS
1

Prerequisites

Before you begin, make sure you have:
  • Node.js and npm installed
  • A Composio account with API key
  • An OpenAI API key
2

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.
3

Install required dependencies

bash
npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv

First, install the necessary packages for your project.

What you're installing:

  • @ai-sdk/openai: Vercel AI SDK's OpenAI provider
  • @ai-sdk/mcp: MCP client for Vercel AI SDK
  • @composio/core: Composio SDK for tool integration
  • ai: Core Vercel AI SDK
  • dotenv: Environment variable management
4

Set up environment variables

bash
OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here

Create a .env file in your project root.

What's needed:

  • OPENAI_API_KEY: Your OpenAI API key for GPT model access
  • COMPOSIO_API_KEY: Your Composio API key for tool access
  • COMPOSIO_USER_ID: A unique identifier for the user session
5

Import required modules and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});
What's happening:
  • We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
  • The dotenv/config import automatically loads environment variables
  • The MCP client import enables connection to Composio's tool server
6

Create Tool Router session and initialize MCP client

typescript
async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["elevenreader"],
  });

  const mcpUrl = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Elevenreader tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned mcp object contains the URL and authentication headers needed to connect to the MCP server
  • This session provides access to all Elevenreader-related tools through the MCP protocol
7

Connect to MCP server and retrieve tools

typescript
const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();
What's happening:
  • We're creating an MCP client that connects to our Composio Tool Router session via HTTP
  • The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
  • The type: "http" is important - Composio requires HTTP transport
  • tools() retrieves all available Elevenreader tools that the agent can use
8

Initialize conversation and CLI interface

typescript
let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to elevenreader, like summarize my last 5 emails, send an email, etc... :)))\n",
);

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();
What's happening:
  • We initialize an empty messages array to maintain conversation history
  • A readline interface is created to accept user input from the command line
  • Instructions are displayed to guide the user on how to interact with the agent
9

Handle user input and stream responses with real-time tool feedback

typescript
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;
  }

  messages.push({ role: "user", content: trimmedInput });
  console.log("\nAgent is thinking...\n");

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • We use streamText instead of generateText to stream responses in real-time
  • toolChoice: "auto" allows the model to decide when to use Elevenreader tools
  • stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
  • onStepFinish callback displays which tools are being used in real-time
  • We iterate through the text stream to create a typewriter effect as the agent responds
  • The complete response is added to conversation history to maintain context
  • Errors are caught and displayed with helpful retry suggestions

Complete Code

Here's the complete code to get you started with Elevenreader and Vercel AI SDK:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["elevenreader"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to elevenreader, like summarize my last 5 emails, send an email, etc... :)))\n",
  );

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  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;
    }

    messages.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});

Conclusion

You've successfully built a Elevenreader agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.

Key features of this implementation:

  • Real-time streaming responses for a better user experience with typewriter effect
  • Live tool execution feedback showing which tools are being used as the agent works
  • Dynamic tool loading through Composio's Tool Router with secure authentication
  • Multi-step tool execution with configurable step limits (up to 10 steps)
  • Comprehensive error handling for robust agent execution
  • Conversation history maintenance for context-aware responses

You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
TOOLS

Supported Tools

Every Elevenreader action and event your agent gets out of the box.

Add Documentation To Knowledge Base

Tool to add documentation to a conversational AI agent's knowledge base.

Add Pronunciation Dictionary From File

Tool to add a pronunciation dictionary from a .

Add Pronunciation Dictionary From Rules

Tool to add a pronunciation dictionary from rules in ElevenLabs.

Add Pronunciation Dictionary Rules

Tool to add pronunciation rules to an ElevenLabs pronunciation dictionary.

Add Shared Voice

Tool to add a shared voice from another user's public library to your own voice library.

Add Tool

Tool to add a conversational AI tool to ElevenLabs ConvAI.

Calculate Public LLM Expected Cost

Tool to calculate expected LLM usage costs based on prompt length, knowledge base size, and RAG configuration.

Cancel batch call

Tool to cancel an active batch call operation.

Compute RAG Index

Tool to compute RAG index for a knowledge base document.

Create Agent

Tool to create a conversational AI agent with ElevenLabs.

Create Agent Response Test

Tool to create an agent response test for testing conversational AI agents.

Create Audio Native Project

Tool to create an Audio Native enabled project on ElevenLabs.

Create Batch Call

Tool to submit a batch call request to ElevenLabs ConvAI.

Create File Document

Tool to create a file document in the ElevenLabs knowledge base.

Create Folder

Tool to create a folder in the ElevenLabs knowledge base.

Create Convai Workspace Secret

Tool to create a Convai workspace secret in ElevenLabs.

Create Text Document

Tool to create a text document in the ElevenLabs knowledge base.

Create URL Document

Tool to create a URL document in the ElevenLabs knowledge base.

Delete Agent

Tool to permanently delete an agent from ElevenLabs.

Delete Batch Call

Tool to delete a specific batch call.

Delete Agent Response Test

Tool to delete an agent response test.

Delete Conversation

Tool to delete a conversation by its unique ID.

Delete Dubbing

Tool to permanently delete a dubbing project by its ID.

Delete Knowledge Base Document

Tool to permanently delete a document from the knowledge base.

Delete Phone Number

Tool to permanently delete a phone number from ElevenLabs ConvAI.

Delete RAG Index

Tool to permanently delete a RAG index from a knowledge base document.

Delete Convai Workspace Secret

Tool to delete a specific Convai workspace secret.

Delete Speech History Item

Tool to permanently delete a speech history item by its ID.

Delete Tool

Tool to permanently delete a conversational AI tool from ElevenLabs.

Delete Transcript By Id

Tool to permanently delete a speech-to-text transcript by its ID.

Download Speech History Items

Tool to download speech history items from ElevenLabs.

Duplicate Agent

Tool to duplicate an existing agent.

Edit Voice

Tool to edit an existing voice in ElevenLabs.

Edit Voice Settings

Tool to edit voice settings for a specific voice in ElevenLabs.

Generate Composition Plan

Tool to generate a music composition plan using ElevenLabs Music API.

Get agent

Tool to retrieve complete details for a specific conversational AI agent by ID.

Get Agent Knowledge Base Size

Tool to retrieve the size of a conversational AI agent's knowledge base.

Get Agent Shareable Link

Tool to get a shareable link for a conversational AI agent.

Calculate Agent LLM Expected Cost

Tool to calculate expected LLM usage costs for a conversational AI agent.

Get Agent Response Test

Tool to retrieve agent response test details by test ID.

Get Agent Response Tests Summaries

Tool to retrieve agent response test summaries by test IDs.

Get Agent Summaries

Tool to retrieve summaries for multiple agents by their IDs.

Get Agent Widget Config

Tool to retrieve the widget configuration for a conversational AI agent.

Get Audio From History Item

Tool to retrieve the audio file from a speech history item.

Get Audio Native Project Settings

Tool to retrieve audio native project settings from ElevenLabs.

Get Batch Call By Id

Tool to retrieve a batch call by its ID.

Get conversation history

Tool to retrieve complete conversation details including transcript, metadata, and analysis.

Get Conversations

Tool to retrieve conversations from ElevenLabs Conversational AI.

Get Conversation Signed Link

Tool to get a signed URL for a conversation with an agent.

Get ConvAI dashboard settings

Tool to retrieve ConvAI dashboard settings including configured charts.

Get Documentation From Knowledge Base

Tool to retrieve a specific document from a conversational AI agent's knowledge base by document ID.

Get Dubbed File

Tool to download a dubbed audio or video file from a dubbing project.

Get Dubbing Metadata

Tool to retrieve metadata for a dubbing project by ID.

Get Dubbed Transcript

Tool to retrieve the transcript of a dubbed audio or video file.

Get Dubbing Transcripts

Tool to retrieve transcripts from a dubbing project in various formats.

Get Generate Voice Parameters

Tool to retrieve voice generation parameters from ElevenLabs.

Get Knowledge Base Content

Tool to retrieve the text content of a knowledge base document by ID.

Get Knowledge Base Dependent Agents

Tool to retrieve the list of conversational AI agents that depend on a specific knowledge base document.

Get Knowledge Base Source File URL

Tool to retrieve a signed URL for downloading the source file of a document from the knowledge base.

Get Knowledge Base Summaries

Tool to retrieve summaries for multiple knowledge base documents by their IDs.

Get Library Voices

Tool to retrieve shared voices from the ElevenLabs voice library.

Get Live Count

Tool to retrieve the count of active ongoing conversations.

Get Models

Tool to retrieve available ElevenLabs speech synthesis models.

Get Or Create RAG Indexes

Tool to compute or retrieve RAG indexes for knowledge base documents in batch.

Get phone number

Tool to retrieve details for a specific phone number by ID.

Get Pronunciation Dictionaries

Tool to get a list of pronunciation dictionaries and their metadata.

Get Pronunciation Dictionary Metadata

Tool to retrieve metadata for a specific pronunciation dictionary by ID.

Get Pronunciation Dictionary Version PLS

Tool to download a PLS file with pronunciation dictionary version rules.

Get RAG Indexes

Tool to retrieve RAG indexes for a specific knowledge base document.

Get RAG Index Overview

Tool to retrieve an overview of the RAG (Retrieval-Augmented Generation) index.

Get Resource Metadata

Tool to retrieve metadata and sharing permissions for a workspace resource.

Get ConvAI workspace secrets

Tool to retrieve ConvAI workspace secrets with pagination support.

Get ConvAI workspace settings

Tool 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 Voices

Tool to find similar voices from the ElevenLabs library by uploading an audio sample.

Get Single Use Token

Tool to create a single-use token for ElevenLabs API.

Get Speech History

Tool to list generated speech history items from ElevenLabs.

Get speech history item by ID

Tool to retrieve complete details for a specific speech history item by ID.

Get Test Invocation

Tool to retrieve test invocation details by invocation ID.

Get tool

Tool to retrieve complete details for a specific conversational AI tool by ID.

Get Tool Dependent Agents

Tool to retrieve the list of conversational AI agents that depend on a specific tool.

Get ConvAI Tools

Tool to retrieve ConvAI tools with pagination support.

Get Transcript By ID

Tool to retrieve a speech-to-text transcript by its unique ID.

Get Characters Usage Metrics

Tool to retrieve character usage metrics from ElevenLabs.

Get User Info

Tool to retrieve information about the authenticated user, including subscription details, character limits, and voice quotas.

Get User Subscription Info

Tool to retrieve detailed subscription information for the authenticated user.

Get User Voices V2

Tool to retrieve voices using the V2 API from ElevenLabs.

Get Voice by ID

Tool to retrieve complete details for a specific voice by ID.

Get Voice Settings

Tool to retrieve the current settings for a specific voice.

Get Default Voice Settings

Tool to retrieve default voice settings for speech synthesis.

Get Workspace Batch Calls

Tool to get all batch calls for a workspace.

Get Workspace Service Accounts

Tool to retrieve all service accounts in the workspace.

Handle SIP Trunk Outbound Call

Tool to initiate an outbound call via SIP trunk using ElevenLabs ConvAI.

Import Phone Number

Tool to import a phone number (Twilio or SIP trunk) into ElevenLabs ConvAI.

Isolate Audio Stream

Tool to isolate vocals/speech from audio files using ElevenLabs Audio Isolation API.

List Agent Branches

Tool to list all branches for a specific agent.

List Agent Response Tests

Tool to list agent response tests from ElevenLabs conversational AI.

List Agents

Tool to list conversational AI agents from ElevenLabs.

List Dubs

Tool to list dubbing projects from ElevenLabs.

List Knowledge Bases

Tool to list knowledge base documents from ElevenLabs.

List MCP Servers

Tool to list all MCP (Model Context Protocol) server configurations in the workspace.

List Phone Numbers

Tool to list all phone numbers available in your ElevenLabs ConvAI workspace.

List Test Invocations

Tool to list test invocations for a specific conversational AI agent.

List WhatsApp Accounts

Tool to list all WhatsApp accounts available in your ElevenLabs ConvAI workspace.

List Workspace Webhooks

Tool to list all webhooks configured in your ElevenLabs workspace.

Bulk Move Knowledge Base Entities

Tool to bulk move documents or folders to a target folder in the knowledge base.

Move Knowledge Base Entity

Tool to move a document or folder to a target folder in the knowledge base.

Patch Agent Settings

Tool to patch (partially update) an agent's settings.

Update Pronunciation Dictionary

Tool to update a pronunciation dictionary.

Post Agent Avatar

Tool to upload an avatar image for a conversational AI agent.

Register Twilio Call

Tool to register a Twilio call with ElevenLabs ConvAI and return TwiML.

Remove Pronunciation Dictionary Rules

Tool to remove rules from a pronunciation dictionary.

Resubmit Tests

Tool to resubmit failed or specific tests from a previous test invocation.

Retry batch call

Tool to retry a failed or cancelled batch call.

Run Agent Test Suite

Tool to run tests on a conversational AI agent.

Run Conversation Simulation

Tool 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 Test

Tool to update an existing agent response test in ElevenLabs ConvAI.

Update Audio Native Project Content

Tool to update audio-native project content by uploading a new txt or HTML file.

Update ConvAI Settings

Tool to update ConvAI workspace settings in ElevenLabs.

Update ConvAI dashboard settings

Tool to update ConvAI dashboard settings including chart configurations.

Update Document

Tool to update a document in the ElevenLabs knowledge base.

Update Phone Number

Tool to update a phone number's configuration in ElevenLabs ConvAI.

Update Convai Workspace Secret

Tool to update a Convai workspace secret by ID.

Update Tool

Tool to update a conversational AI tool configuration.

FRAMEWORKS

How to build Elevenreader MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Elevenreader MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Elevenreader MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Elevenreader MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Elevenreader MCP with Claude Cowork

Codex logo

Codex

Use Elevenreader MCP with Codex

OpenClaw logo

OpenClaw

Use Elevenreader MCP with OpenClaw

Hermes logo

Hermes

Use Elevenreader MCP with Hermes

CLI logo

CLI

Use Elevenreader MCP with CLI

Google ADK logo

Google ADK

Use Elevenreader MCP with Google ADK

LangChain logo

LangChain

Use Elevenreader MCP with LangChain

Mastra AI logo

Mastra AI

Use Elevenreader MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Elevenreader MCP with LlamaIndex

CrewAI logo

CrewAI

Use Elevenreader MCP with CrewAI

FAQ

Frequently asked questions

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.

Yes, you can. Vercel AI SDK v6 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.

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.

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.

Start with Elevenreader.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Elevenreader tool your agent needs.Free to start.

Start building
Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREEBOOK A DEMO
agent.aiZoomLettaGleanHubSpotAWSWabi

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies