How to integrate Render MCP with Autogen

This guide walks you through connecting Render to AutoGen using the Composio tool router. By the end, you'll have a working Render agent that can deploy latest code to staging service, restart production web service now, get current status of all services through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Render account through Composio's Render MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Render is a unified cloud platform for building and running apps and websites. It simplifies deployment, scaling, and management across your projects.

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Introduction

This guide walks you through connecting Render to AutoGen using the Composio tool router. By the end, you'll have a working Render agent that can deploy latest code to staging service, restart production web service now, get current status of all services through natural language commands.

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

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

Also integrate Render with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle 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 Render
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Render tools
  • Run a live chat loop where you ask the agent to perform Render 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 Render MCP server, and what's possible with it?

The Render MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Render account. It provides structured and secure access to your cloud infrastructure, so your agent can perform actions like deploying applications, managing services, monitoring site health, restarting instances, and scaling resources on your behalf.

  • Automated application deployment: Instantly deploy new web apps or services without manual steps, letting your agent handle setup and rollouts.
  • Service monitoring and status checks: Ask your agent to check the health and uptime of your apps or services, so you’re always up to speed on what’s running smoothly—and what’s not.
  • Instance management and restarts: Enable your agent to restart, stop, or scale up/down your running services to quickly respond to changes or issues.
  • Resource scaling and configuration: Let your agent adjust resource allocations, increasing or decreasing capacity based on current needs or traffic spikes.
  • Error diagnostics and log retrieval: Have your agent fetch logs or error reports to help troubleshoot issues before they become major problems.

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 Render 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 Render 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 Render 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 Render session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["render"]
    )
    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 Render 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 Render assistant agent with MCP tools
    agent = AssistantAgent(
        name="render_assistant",
        description="An AI assistant that helps with Render 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 Render 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 Render 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 Render 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 Render 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 Render session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["render"]
    )
    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 Render assistant agent with MCP tools
        agent = AssistantAgent(
            name="render_assistant",
            description="An AI assistant that helps with Render 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 Render 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 Render 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 Render, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Add Header Rule

Tool to add a custom HTTP header rule to a Render service.

Add or Update Secret File

Tool to add or update a secret file for a Render service.

Add Resources to Environment

Tool to add resources to a Render environment.

Add Route

Tool to add redirect or rewrite rules to a Render service.

Create Custom Domain

Tool to add a custom domain to a Render service.

Create Environment Group

Tool to create a new environment group.

Create Environment

Tool to create a new environment within a Render project.

Create Postgres Instance

Tool to create a new Postgres instance on Render.

Create Registry Credential

Tool to create a registry credential.

Delete Environment Group Variable

Tool to remove an environment variable from an environment group.

Delete Environment Group Secret File

Tool to remove a secret file from an environment group.

Delete Environment

Tool to delete a specified environment.

Delete Key Value

Tool to delete a Key Value instance.

Delete Owner Log Stream

Tool to delete a log stream for an owner.

Delete Owner Metrics Stream

Tool to delete a metrics stream for a workspace.

Delete Registry Credential

Tool to delete a registry credential.

Delete Secret File

Tool to delete a secret file from a Render service.

Delete Service

Tool to delete a service.

Disconnect Blueprint

Tool to disconnect a blueprint from your Render account.

Get Active Connections

Tool to get active connection count metrics for Render resources.

Get Bandwidth Sources

Tool to get bandwidth usage breakdown by traffic source.

Get CPU Usage

Tool to retrieve CPU usage metrics for Render resources.

Get CPU Limit

Tool to retrieve CPU limit metrics for Render resources.

Get Disk Capacity

Tool to get disk capacity metrics for Render resources.

Get Disk Usage

Tool to retrieve disk usage metrics for Render resources.

Get Instance Count

Tool to get instance count metrics for Render resources.

Get Memory Usage

Tool to get memory usage metrics for one or more resources.

Get Memory Limit

Tool to get memory limit metrics for Render resources over a specified time range.

Get Memory Target

Tool to get memory target metrics for Render resources.

Get User

Tool to get the authenticated user.

Link Service to Environment Group

Tool to link a service to an environment group.

List Application Filter Values

Tool to list queryable instance values for application metrics.

List Blueprints

Tool to list all blueprints.

List Deploys

Tool to list recent deploys for a Render service with pagination and filtering.

List Disks

Tool to list all disks.

List Environment Groups

Tool to list environment groups.

List Environments

Tool to list environments for a project.

List Environment Variables for Service

Tool to list all environment variables configured directly on a Render service (with pagination).

List Instances

Tool to list instances of a service.

List Key Value Instances

Tool to list all Key Value instances.

List Logs

Tool to list logs for a specific workspace and resource.

List Log Label Values

Tool to list log label values for a workspace.

List Maintenance Runs

Tool to list maintenance runs.

List Notification Overrides

Tool to list notification overrides for services.

List Workspace Members

Tool to list workspace members.

List Owners

Tool to list owners (users and teams).

List Postgres Instances

Tool to list Postgres instances.

List Postgres Exports

Tool to list all exports for a Postgres instance.

List PostgreSQL Users

Tool to list PostgreSQL user credentials for a Render PostgreSQL database instance.

List Projects

List Projects

List Registry Credentials

Tool to list registry credentials.

List Resource Log Streams

Tool to list resource log stream overrides.

List Routes

Tool to list redirect/rewrite rules for a service.

List Secret Files

Tool to list secret files for a Render service.

List Services

Tool to list all services.

List Task Runs

Tool to list task runs.

List Tasks

Tool to list tasks.

List Webhooks

Tool to list all webhooks.

List Workflows

Tool to list workflows.

List Workflow Versions

Tool to list workflow versions.

Restart Service

Tool to restart a service.

Resume Service

Tool to resume a suspended service.

Retrieve Custom Domain

Tool to retrieve a specific custom domain for a service.

Retrieve deploy

Retrieve deploy

Retrieve Environment Group

Tool to retrieve a specific environment group by ID.

Retrieve Environment Variable

Tool to retrieve a specific environment variable from a Render environment group.

Retrieve Environment Group Secret File

Tool to retrieve secret file from an environment group.

Retrieve Environment Variable

Tool to retrieve a specific environment variable from a Render service.

Retrieve Owner

Tool to retrieve a specific owner (workspace) by ID.

Retrieve Owner Notification Settings

Tool to retrieve notification settings for a specific owner (workspace).

Retrieve Postgres Instance

Tool to retrieve a specific Postgres instance.

Retrieve Project

Tool to retrieve a specific project by ID.

Retrieve Registry Credential

Tool to retrieve a registry credential by ID.

Retrieve Secret File

Tool to retrieve a secret file from a Render service.

Retrieve Service

Tool to retrieve a specific service by ID.

Stream Task Runs Events

Tool to stream real-time task run events via Server-Sent Events (SSE).

Subscribe to Logs

Tool to subscribe to real-time logs via WebSocket connection.

Suspend Service

Tool to suspend a service.

Trigger Deploy

Tool to trigger a new deploy for a specified service.

Update Environment Group

Tool to update an environment group's name.

Update Environment Group Variable

Tool to add or update an environment variable in an environment group.

Update Environment Group Secret File

Tool to add or update a secret file in an environment group.

Update Environment Variable

Tool to add or update an environment variable for a Render service.

Update Environment Variables for Service

Tool to update environment variables for a Render service.

Update Header Rules

Tool to replace all header rules for a Render service.

Update Owner Log Stream

Tool to update log stream configuration for an owner.

Update Owner Notification Settings

Tool to update notification settings for a specific owner (workspace).

Update Postgres Instance

Tool to update a Postgres instance configuration.

Update Project

Tool to update a project's name.

Update Registry Credential

Tool to update a registry credential.

Update Resource Log Stream

Tool to update log stream override for a resource.

Update Routes

Tool to update redirect/rewrite rules for a service.

Update Secret Files for Service

Tool to update secret files for a Render service.

Update Service

Tool to update a service configuration.

Verify Custom Domain

Tool to verify DNS configuration for a custom domain.

FRAMEWORKS

How to build Render MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Render MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Render MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Render MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Render MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Render MCP with Claude Cowork

Codex logo

Codex

Use Render MCP with Codex

Cursor logo

Cursor

Use Render MCP with Cursor

OpenClaw logo

OpenClaw

Use Render MCP with OpenClaw

Hermes logo

Hermes

Use Render MCP with Hermes

CLI logo

CLI

Use Render MCP with CLI

Google ADK logo

Google ADK

Use Render MCP with Google ADK

LangChain logo

LangChain

Use Render MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Render MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Render MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Render MCP with LlamaIndex

CrewAI logo

CrewAI

Use Render MCP with CrewAI

OpenCode logo

OpenCode

Use Render MCP with OpenCode

VS Code logo

VS Code

Use Render MCP with VS Code

FAQ

Frequently asked questions

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

Yes, absolutely. You can configure which Render 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 Render 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.

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