How to integrate Svix MCP with Autogen

This guide walks you through connecting Svix to AutoGen 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 AutoGen 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.

37 Tools

Introduction

This guide walks you through connecting Svix to AutoGen 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 AutoGen 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 ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Svix
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Svix tools
  • Run a live chat loop where you ask the agent to perform Svix operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Svix account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Svix via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Svix connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Svix session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["svix"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Svix tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Svix assistant agent with MCP tools
    agent = AssistantAgent(
        name="svix_assistant",
        description="An AI assistant that helps with Svix operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Svix tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Svix related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Svix tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Svix and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Svix session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["svix"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Svix assistant agent with MCP tools
        agent = AssistantAgent(
            name="svix_assistant",
            description="An AI assistant that helps with Svix operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Svix related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Svix through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Svix, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
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

LangChain logo

LangChain

Use Svix MCP with LangChain

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. Autogen 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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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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