How to integrate Synthflow ai MCP with LangChain

This guide walks you through connecting Synthflow ai to LangChain using the Composio tool router. By the end, you'll have a working Synthflow ai agent that can create a new ai assistant for customer support, list all current voice assistants in your account, fetch details for team 'sales outreach' through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Synthflow ai account through Composio's Synthflow ai MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Synthflow ai is an AI-powered voice automation platform for inbound and outbound customer calls. It boosts engagement and streamlines operational efficiency with conversational voice agents.

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Introduction

This guide walks you through connecting Synthflow ai to LangChain using the Composio tool router. By the end, you'll have a working Synthflow ai agent that can create a new ai assistant for customer support, list all current voice assistants in your account, fetch details for team 'sales outreach' through natural language commands.

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

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

Also integrate Synthflow ai with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Synthflow ai project to Composio
  • Create a Tool Router MCP session for Synthflow ai
  • Initialize an MCP client and retrieve Synthflow ai tools
  • Build a LangChain agent that can interact with Synthflow 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 Synthflow ai MCP server, and what's possible with it?

The Synthflow 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 Synthflow ai account. It provides structured and secure access to your voice automation tools, so your agent can perform actions like managing voice assistants, handling teams, retrieving phone numbers, and automating call center operations on your behalf.

  • AI assistant management: Create, list, update, or delete AI-powered voice assistants to tailor customer interactions and automate call flows as needed.
  • Team creation and configuration: Set up new teams, modify existing ones, or remove teams to optimize your call center's routing and operational structure.
  • Knowledge base integration: Retrieve and manage knowledge base details to ensure your assistants have accurate, up-to-date information for conversations.
  • Phone number administration: Fetch and organize phone numbers linked to your workspace, making it easy to assign or reassign numbers for inbound and outbound campaigns.
  • Comprehensive assistant and team insights: Access detailed metadata and configuration for both assistants and teams, streamlining oversight and decision-making for your AI-powered operations.

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 step10 STEPS
1

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
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 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
4

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
5

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 Synthflow ai functionality through MCP
6

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 Synthflow ai tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

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

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Synthflow 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 Synthflow ai tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "synthflow_ai-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 Synthflow ai MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Synthflow ai tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

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 Synthflow 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
10

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 Synthflow 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: ['synthflow_ai']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "synthflow_ai-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 Synthflow 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 Synthflow 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 Synthflow ai action and event your agent gets out of the box.

Add document to knowledge base source

Tool to add a document to a knowledge base source.

Attach Actions to Agent

Tool to attach one or more actions to an agent.

Attach contact to memory store

Tool to attach a contact to a memory store.

Attach knowledge base to agent

Tool to attach a knowledge base to an agent.

Attach memory store to agent

Tool to attach a memory store to an agent.

Create Action

Tool to create a new action in Synthflow AI.

Create Assistant

Tool to create a new assistant.

Create a contact

Tool to create a new contact in Synthflow AI.

Create knowledge base

Tool to create a new knowledge base and return its ID.

Create memory store

Tool to create a new memory store.

Create Phone Book

Tool to create a new phone book.

Create phone book entry

Tool to create a phone book entry.

Create Simulation Case

Tool to create a new simulation case.

Create a simulation scenario

Tool to create a new simulation scenario.

Create a new simulation suite

Tool to create a new simulation suite attached to a specific agent.

Create a new team

Tool to create a new team.

Delete an action

Tool to delete an existing action.

Delete an assistant

Tool to delete an existing AI assistant.

Delete a chat session

Tool to delete a chat session.

Delete a contact

Tool to delete an existing contact.

Delete knowledge base

Tool to delete an existing knowledge base.

Delete a knowledge base source

Tool to delete a source from a knowledge base.

Delete a memory store

Tool to delete a memory store.

Delete a phone book

Tool to delete an existing phone book.

Delete a phone book entry

Tool to delete a phone book entry.

Delete a simulation case

Tool to delete a simulation case by ID.

Delete a simulation scenario

Tool to delete an existing simulation scenario.

Delete a simulation suite

Tool to delete a simulation suite by ID.

Delete a subaccount

Tool to delete an existing subaccount.

Delete a team

Tool to delete an existing team.

Detach actions from assistant

Tool to detach one or more actions from an AI assistant.

Detach knowledge base

Tool to detach a knowledge base from an AI assistant.

Detach contact from memory store

Tool to detach a contact from a memory store.

Detach memory store from agent

Tool to detach a memory store from an agent.

Execute simulation suite

Tool to execute all test cases in a simulation suite.

Export analytics data

Tool to export analytics data for calls within a specified date range.

Get action metadata

Tool to retrieve metadata about a specific action by its ID.

Get AI assistant details

Tool to retrieve details of a specific AI assistant.

Get phone call details

Tool to retrieve the transcript and detailed metadata for a specific phone call.

Get contact details

Tool to retrieve details of a specific contact by its ID.

Get knowledge base

Tool to retrieve details of a specific knowledge base by its ID.

Get memory store

Tool to retrieve details of a specific memory store by its ID.

Get memory store contact data

Tool to retrieve memory data for a specific contact in a memory store.

Get phone numbers

Tool to retrieve a list of phone numbers associated with a workspace.

Get simulation details

Tool to retrieve details of a specific simulation by ID.

Get Simulation Case

Tool to retrieve a simulation case by ID.

Get simulation scenario

Tool to retrieve a simulation scenario by ID.

Get simulation suite by ID

Tool to retrieve a simulation suite by ID.

Get subaccount details

Tool to retrieve detailed metadata about a specific subaccount by ID.

Get team details

Tool to retrieve details of a specific team by its ID.

Initialize Action

Tool to initialize a custom action with specified variables.

List actions

Tool to list all actions in the workspace.

List AI assistants

Tool to list all AI assistants associated with the account.

List call history

Tool to retrieve call history (call logs) with filtering to check outcomes/statuses after placing calls.

List chats

Tool to retrieve a list of chats, optionally filtered by agent ID.

List contacts

Tool to retrieve a list of contacts with optional search filtering.

List memory stores

Tool to list memory stores with optional filtering by title.

List Phone Books

Tool to list all phone books in your workspace.

List Simulation Cases

Tool to list simulation cases with pagination and optional filtering by name or type.

List simulation cases by agent

Tool to list all simulation cases created for a specific agent.

List simulations

Tool to list simulations with pagination and optional filters.

List simulation scenarios

Tool to list simulation scenarios with pagination and optional filtering.

List simulation sessions

Tool to list simulation sessions with pagination and optional filters.

List simulation suites

Tool to list simulation suites with pagination and optional filtering.

List subaccounts

Tool to list all subaccounts associated with the authenticated account.

List teams

Tool to list assistant teams.

List voices

Tool to list all text-to-speech voices in a workspace.

List webhook logs

Tool to retrieve paginated webhook logs with filtering and search capability.

Make a voice call

Tool to initiate a real-time voice call via the AI agent.

Start Simulation

Tool to start a new simulation using a simulation case.

Update Action

Tool to update an existing action in Synthflow AI.

Update Assistant

Tool to update an existing assistant’s settings.

Update a contact

Tool to update an existing contact in Synthflow AI.

Update knowledge base

Tool to update an existing knowledge base's name or usage conditions.

Update memory store

Tool to update an existing memory store's title and description.

Update Simulation Case

Tool to update an existing simulation case.

Update a simulation scenario

Tool to update an existing simulation scenario.

Update an existing simulation suite

Tool to update an existing simulation suite.

Update an existing team

Tool to update an existing team.

FRAMEWORKS

How to build Synthflow ai MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Synthflow ai MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Synthflow ai MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Synthflow ai MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Synthflow ai MCP with Claude Cowork

Codex logo

Codex

Use Synthflow ai MCP with Codex

OpenClaw logo

OpenClaw

Use Synthflow ai MCP with OpenClaw

Hermes logo

Hermes

Use Synthflow ai MCP with Hermes

CLI logo

CLI

Use Synthflow ai MCP with CLI

Google ADK logo

Google ADK

Use Synthflow ai MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Synthflow ai MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Synthflow ai MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Synthflow ai MCP with LlamaIndex

CrewAI logo

CrewAI

Use Synthflow ai MCP with CrewAI

FAQ

Frequently asked questions

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

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

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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.

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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.

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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.

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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.

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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.

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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.

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Co-Founder, Ingram Technologies