How to integrate Svix MCP with LangChain

This guide walks you through connecting Svix to LangChain using the Composio tool router. By the end, you'll have a working Svix agent that can list all webhook endpoints for app x, create a new webhook endpoint for payments, update application rate limit to 1000/min through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Svix account through Composio's Svix MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Svix is an enterprise-grade webhooks service for sending webhooks reliably and securely. It helps developers deliver, track, and manage webhooks with advanced monitoring and retry logic.

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Introduction

This guide walks you through connecting Svix to LangChain using the Composio tool router. By the end, you'll have a working Svix agent that can list all webhook endpoints for app x, create a new webhook endpoint for payments, update application rate limit to 1000/min through natural language commands.

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

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

Also integrate Svix 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 Svix project to Composio
  • Create a Tool Router MCP session for Svix
  • Initialize an MCP client and retrieve Svix tools
  • Build a LangChain agent that can interact with Svix
  • 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 Svix MCP server, and what's possible with it?

The Svix MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Svix account. It provides structured and secure access to your webhooks infrastructure, so your agent can perform actions like managing applications, configuring endpoints, sending webhooks, and monitoring delivery attempts on your behalf.

  • Application management and automation: Ask your agent to create, update, list, or delete Svix applications, making it easy to manage webhook-enabled projects programmatically.
  • Endpoint configuration: Have your agent register, retrieve, or remove webhook endpoints for your applications, ensuring your events get delivered to the right places.
  • Webhook delivery tracking: Let your agent fetch detailed information about message delivery attempts, helping you monitor reliability and debug failed webhooks with ease.
  • Comprehensive application insights: Retrieve metadata and details for any Svix application, so your agent can surface key info or audit your webhook ecosystem.
  • Automated cleanup and maintenance: Direct your agent to delete outdated applications or endpoints, streamlining your webhook management and reducing clutter.

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 Svix 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 Svix 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: ['svix']
    }
);

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

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "svix-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 Svix MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Svix 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 Svix 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 Svix 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: ['svix']
        }
    );

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

Create Application

Tool to create a new Svix application.

Delete Svix Application

Permanently delete a Svix application by its ID or UID.

Get Application

Tool to retrieve details of a specific Svix application by its ID.

List Applications

Tool to list all applications.

Update Svix Application

Tool to update an existing Svix application by ID.

Get Attempt Details

Tool to retrieve details of a specific message attempt.

List Message Attempts

Tool to list all delivery attempts for a specific message.

Create Endpoint

Tool to create a new Svix webhook endpoint.

Delete Endpoint

Tool to delete an endpoint.

Get Endpoint

Tool to retrieve details of a specific endpoint.

List Endpoints

Tool to list all endpoints for a specific application.

Patch Endpoint

Tool to partially update an endpoint’s configuration.

Patch Endpoint Headers

Tool to partially update headers for a specific endpoint.

Recover Failed Webhooks

Tool to recover messages that failed to send to an endpoint.

Replay Missing Webhooks

Tool to replay missing webhooks for a specific endpoint.

Get Endpoint Secret

Tool to retrieve the secret for a specific endpoint.

Rotate Endpoint Secret

Tool to rotate the signing secret key for an endpoint.

Send Example Message

Tool to send a test message for a specific event type to an endpoint.

Get Endpoint Stats

Tool to retrieve basic statistics for a specific endpoint.

Get Endpoint Transformation

Tool to retrieve transformation settings for a specific endpoint.

Set Endpoint Transformation

Tool to set or update transformation settings for an endpoint.

Update Endpoint

Tool to update an existing endpoint or create it if it doesn't exist (upsert).

Update Endpoint Headers

Tool to completely replace headers for a specific endpoint.

Create Event Type

Create a new event type in Svix or unarchive an existing one.

Delete Event Type

Tool to delete an event type.

Get Event Type

Retrieve details of a specific event type by its name.

List Event Types

Tool to retrieve a list of all event types.

Update Event Type

Update an existing event type's description, schema, feature flags, or archive status.

Create Integration

Tool to create a new integration for a specific application.

Delete Integration

Permanently delete an integration from a Svix application.

Get Integration

Tool to retrieve details of a specific integration.

List Integrations

Tool to list all integrations for a specific application.

Update Integration

Tool to update an existing integration by ID.

Create Message

Tool to create a new message for a specific application in Svix.

Get Message

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

List Messages

Tool to list all messages for a specific application.

Create Source

Creates a new Svix Ingest source for receiving webhooks from external providers.

FRAMEWORKS

How to build Svix MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Svix MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Svix MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Svix MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Svix MCP with Claude Cowork

Codex logo

Codex

Use Svix MCP with Codex

OpenClaw logo

OpenClaw

Use Svix MCP with OpenClaw

Hermes logo

Hermes

Use Svix MCP with Hermes

CLI logo

CLI

Use Svix MCP with CLI

Google ADK logo

Google ADK

Use Svix MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Svix MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Svix MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Svix MCP with LlamaIndex

CrewAI logo

CrewAI

Use Svix MCP with CrewAI

FAQ

Frequently asked questions

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

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

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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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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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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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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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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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