How to integrate Rev AI MCP with LangChain

Connect LangChain to Rev AI MCP. Transcribe uploaded "team_meeting.mp3" audio file, get caption file for latest transcript, and more using natural language, with authentication handled for you.

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Rev AI is a speech-to-text platform offering high-quality transcripts, captions, and subtitles. It's known for combining human expertise with AI for accurate, affordable results.

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Introduction

This guide walks you through connecting Rev AI to LangChain using the Composio tool router. By the end, you'll have a working Rev AI agent that can transcribe uploaded "team_meeting.mp3" audio file, get caption file for latest transcript, check status of transcript for order 12345 through natural language commands.

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

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

Also integrate Rev AI with

Claude Code Claude Cowork OpenAI Agents SDK Claude Agent SDK Codex OpenClaw Hermes Atomic Agent Google ADK Vercel AI SDK Mastra AI LlamaIndex CrewAI Pydantic AI AutoGen

TL;DR

Here's what you'll learn:

Get and set up your OpenAI and Composio API keys
Connect your Rev AI project to Composio
Create a Tool Router MCP session for Rev AI
Initialize an MCP client and retrieve Rev AI tools
Build a LangChain agent that can interact with Rev AI
Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

Agent Framework: Build agents that can use tools and make decisions
MCP Integration: Connect to external services through Model Context Protocol adapters
Memory Management: Maintain conversation history across interactions
Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

What is the Rev AI MCP server, and what's possible with it?

The Rev AI MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Rev AI account. It provides structured and secure access to your transcription and speech analysis workflows, so your agent can transcribe recordings, generate captions, translate transcripts, identify languages, and analyze topics and sentiment on your behalf.

Audio and video transcription: Have your agent submit recorded media for transcription, check its progress, retrieve completed transcripts, and generate concise summaries.
Captions and translations: Let the agent retrieve captions in SRT or VTT format and fetch translated captions or transcripts for completed recordings.
Live transcription: Direct your agent to create live RTMP sessions or start WebSocket streams for real-time transcription of audio and video.
Language and speech alignment: Instruct your agent to identify the language spoken in a recording or align existing transcript text with its source audio.
Topic and sentiment analysis: Have your agent analyze text or transcripts to identify key themes and detect positive, negative, or neutral sentiment.

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:

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

Step-by-step Guide

Step by step10 STEPS

Prerequisites

Before starting this tutorial, make sure you have:

Python 3.10 or higher installed on your system
A Composio account with an API key
An OpenAI API key
Basic familiarity with Python and async programming

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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

@composio/langchain provides Composio integration for LangChain
@langchain/mcp-adapters enables MCP client connections
@langchain/core is the core agent framework
dotenv/config loads environment variables

Set up environment variables

bash

COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

COMPOSIO_API_KEY authenticates your requests to Composio's API
COMPOSIO_USER_ID identifies the user for session management
OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();

What's happening:

We're importing LangChain's MCP adapter and Composio SDK
The dotenv/config import loads environment variables from your .env file
This setup prepares the foundation for connecting LangChain with Rev AI functionality through MCP

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

What's happening:

We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
Creating a Composio instance that will manage our connection to Rev AI tools
Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

const url = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Rev AI tools
The create method takes the user ID and specifies which toolkits should be available
The returned session.mcp.url is the MCP server URL that your agent will use
This approach allows the agent to dynamically load and use Rev AI tools as needed

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "rev-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });

What's happening:

We're creating a MultiServerMCPClient that connects to our Rev AI MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Rev AI tools that the agent can use
We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Rev AI related question or task to the agent.\n");

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

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

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

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

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

What's happening:

We initialize an empty conversationHistory list to maintain context across interactions
A readline interface is used to continuously accept user input from the command line
When a user types a message, it's added to the conversation history and sent to the agent
The agent processes the request using the invoke() method with the full conversation history
Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

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

What's happening:

We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Rev AI and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

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

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "rev-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Rev AI related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

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

Conclusion

You've successfully built a LangChain agent that can interact with Rev AI through Composio's Tool Router.

Key features of this implementation:

Dynamic tool loading through Composio's Tool Router
Conversation history maintenance for context-aware responses
Async Python provides clean, efficient execution of agent workflows

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

TOOLS

Supported Tools

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

Create RTMP Stream

Tool to create an RTMP live stream session for real-time transcription of live audio/video streams.

Delete Alignment Job

Tool to delete a forced alignment job and its associated data.

Delete Custom Vocabulary

Tool to delete a completed custom vocabulary and its data.

Delete Job By ID

Tool to delete a completed transcription job and its data.

Delete Language ID Job

Tool to delete a language identification job and its associated data.

Delete Sentiment Analysis Job

Tool to delete a specific sentiment analysis job and its associated data.

Delete Topic Extraction Job

Tool to delete a topic extraction job and its associated data.

Get Account

Retrieves Rev AI account information including email, credit balance (in hours), and HIPAA status.

Get Alignment Job

Tool to get details of a specific forced alignment job including its status.

Get Alignment Transcript

Tool to retrieve the aligned transcript with timestamps for a completed alignment job.

Get Captions

Tool to retrieve captions (SRT or VTT) for a completed Rev.

Get Captions Translation

Tool to retrieve translated captions for a completed Rev.

Get Custom Vocabulary Details

Tool to retrieve custom vocabulary processing details.

Get Job by ID

Tool to fetch details of a transcription job by its ID.

Get Language ID Job

Tool to fetch details of a language identification job by its ID.

Get Language Identification Result

Tool to retrieve language identification results for a completed job.

Get List of Jobs

Retrieves a list of transcription jobs from the past 30 days in reverse chronological order (newest first).

Get Sentiment Job

Tool to fetch details of a sentiment analysis job by its ID.

Get Sentiment Analysis Result

Tool to retrieve sentiment analysis results for a completed Rev.

Get Topic Extraction Result

Tool to retrieve topic extraction results for a completed job.

Get Topic Job

Tool to fetch details of a topic extraction job by its ID.

Get Transcript by ID

Tool to retrieve the transcript of a completed Rev.

Get Transcript Summary

Tool to retrieve a summary of the transcript for a completed transcription job.

Get Transcript Translation

Tool to retrieve a translated version of the transcript for a completed Rev.

List Alignment Jobs

Tool to retrieve a list of all forced alignment jobs for the account.

List Custom Vocabularies

Tool to retrieve a list of all custom vocabularies for the account.

List Language Identification Jobs

Tool to retrieve a list of language identification jobs for the account.

List Sentiment Analysis Jobs

Tool to retrieve a list of all sentiment analysis jobs for the account.

List Topic Extraction Jobs

Tool to retrieve a list of all topic extraction jobs for the account.

Start Stream Transcription

Tool to start a WebSocket transcription stream.

Submit Alignment Job

Tool to submit an audio file with existing transcript for forced alignment.

Submit Custom Vocabulary

Submits a custom vocabulary to Rev.

Submit Language ID Job

Tool to submit an audio file for language identification to detect the spoken language.

Submit Sentiment Analysis Job

Submit text for sentiment analysis to detect positive, negative, or neutral sentiments.

Submit Topic Extraction Job

Tool to submit text or transcripts for topic extraction to identify key topics and themes.

Submit Transcription Job

Submit an audio or video file for asynchronous transcription using Rev.

FRAMEWORKS

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OpenAI Agents SDK

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OpenClaw

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Hermes

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Atomic Agent

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Google ADK

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Vercel AI SDK

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Mastra AI

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LlamaIndex

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CrewAI

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Pydantic AI

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AutoGen

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MORE TOOLKITS

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Toolkit marketplace

Google Drive

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Google Sheets

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Composio

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Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.

Notion

Oauth2Api Key

Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.

FAQ

Frequently asked questions

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

Yes, you can. LangChain fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Rev AI tools.

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

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How to integrate Rev AI MCP with LangChain

Connect Rev AI without auth hassles

Introduction

Also integrate Rev AI with

TL;DR

What is LangChain?

What is the Rev AI MCP server, and what's possible with it?

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Initialize Composio client

Create a Tool Router session

Configure the agent with the MCP URL

Set up interactive chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Rev AI MCP Agent with another framework

Claude Code

Claude Cowork

OpenAI Agents SDK

Claude Agent SDK

Codex

OpenClaw

Hermes

Atomic Agent

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Google Drive

Google Sheets

Composio

Notion

Frequently asked questions

What are the differences in Tool Router MCP and Rev AI MCP?+

Can I use Tool Router MCP with LangChain?+

Can I manage the permissions and scopes for Rev AI while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Rev AI.It takes 30 seconds.