How to integrate Render MCP with Vercel AI SDK v6

This guide walks you through connecting Render to Vercel AI SDK v6 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 Vercel AI SDK 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

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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 will help you understand how to give your Vercel AI SDK 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

ChatGPT OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenCode Cursor VS Code OpenClaw Hermes CLI Google ADK LangChain Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

How to set up and configure a Vercel AI SDK agent with Render integration
Using Composio's Tool Router to dynamically load and access Render tools
Creating an MCP client connection using HTTP transport
Building an interactive CLI chat interface with conversation history management
Handling tool calls and results within the Vercel AI SDK framework

What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.

Key features include:

streamText: Core function for streaming responses with real-time tool support
MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
OpenAI Provider: Native integration with OpenAI models

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:

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 step09 STEPS

Prerequisites

Before you begin, make sure you have:

Node.js and npm installed
A Composio account with API key
An OpenAI API key

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 required dependencies

bash

npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv

First, install the necessary packages for your project.

What you're installing:

@ai-sdk/openai: Vercel AI SDK's OpenAI provider
@ai-sdk/mcp: MCP client for Vercel AI SDK
@composio/core: Composio SDK for tool integration
ai: Core Vercel AI SDK
dotenv: Environment variable management

Set up environment variables

bash

OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here

Create a .env file in your project root.

What's needed:

OPENAI_API_KEY: Your OpenAI API key for GPT model access
COMPOSIO_API_KEY: Your Composio API key for tool access
COMPOSIO_USER_ID: A unique identifier for the user session

Import required modules and validate environment

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

What's happening:

We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
The dotenv/config import automatically loads environment variables
The MCP client import enables connection to Composio's tool server

Create Tool Router session and initialize MCP client

typescript

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["render"],
  });

  const mcpUrl = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Render tools
The create method takes the user ID and specifies which toolkits should be available
The returned mcp object contains the URL and authentication headers needed to connect to the MCP server
This session provides access to all Render-related tools through the MCP protocol

Connect to MCP server and retrieve tools

typescript

const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();

What's happening:

We're creating an MCP client that connects to our Composio Tool Router session via HTTP
The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
The type: "http" is important - Composio requires HTTP transport
tools() retrieves all available Render tools that the agent can use

Initialize conversation and CLI interface

typescript

let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to render, like summarize my last 5 emails, send an email, etc... :)))\n",
);

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

rl.prompt();

What's happening:

We initialize an empty messages array to maintain conversation history
A readline interface is created to accept user input from the command line
Instructions are displayed to guide the user on how to interact with the agent

Handle user input and stream responses with real-time tool feedback

typescript

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;
  }

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

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

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

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

What's happening:

We use streamText instead of generateText to stream responses in real-time
toolChoice: "auto" allows the model to decide when to use Render tools
stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
onStepFinish callback displays which tools are being used in real-time
We iterate through the text stream to create a typewriter effect as the agent responds
The complete response is added to conversation history to maintain context
Errors are caught and displayed with helpful retry suggestions

Complete Code

Here's the complete code to get you started with Render and Vercel AI SDK:

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["render"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to render, like summarize my last 5 emails, send an email, etc... :)))\n",
  );

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

  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;
    }

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

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

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

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

Conclusion

You've successfully built a Render agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.

Key features of this implementation:

Real-time streaming responses for a better user experience with typewriter effect
Live tool execution feedback showing which tools are being used as the agent works
Dynamic tool loading through Composio's Tool Router with secure authentication
Multi-step tool execution with configurable step limits (up to 10 steps)
Comprehensive error handling for robust agent execution
Conversation history maintenance for context-aware responses

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

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 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 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

Use Render MCP with ChatGPT

OpenAI Agents SDK

Use Render MCP with OpenAI Agents SDK

Claude Agent SDK

Use Render MCP with Claude Agent SDK

Claude Code

Use Render MCP with Claude Code

Claude Cowork

Use Render MCP with Claude Cowork

Codex

Use Render MCP with Codex

Cursor

Use Render MCP with Cursor

OpenClaw

Use Render MCP with OpenClaw

Hermes

Use Render MCP with Hermes

CLI

Use Render MCP with CLI

Google ADK

Use Render MCP with Google ADK

LangChain

Use Render MCP with LangChain

Mastra AI

Use Render MCP with Mastra AI

LlamaIndex

Use Render MCP with LlamaIndex

CrewAI

Use Render MCP with CrewAI

OpenCode

Use Render MCP with OpenCode

VS Code

Use Render MCP with VS Code

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Supabase

Oauth2Api Key

Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure.

Codeinterpreter

No Auth

Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms.

GitHub

Oauth2

GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place.

Ably

Api Key

Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.

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. Vercel AI SDK v6 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.

Start with Render.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Render tool your agent needs.Free to start.

Start building

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

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

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

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

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

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

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

Co-Founder, Ingram Technologies

How to integrate Render MCP with Vercel AI SDK v6

Connect Render without auth hassles

Introduction

Also integrate Render with

TL;DR

What is Vercel AI SDK?

What is the Render 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 required dependencies

Set up environment variables

Import required modules and validate environment

Create Tool Router session and initialize MCP client

Connect to MCP server and retrieve tools

Initialize conversation and CLI interface

Handle user input and stream responses with real-time tool feedback

Complete Code

Conclusion

Supported Tools

How to build Render MCP Agent with another framework

ChatGPT

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

Cursor

OpenClaw

Hermes

CLI

Google ADK

LangChain

Mastra AI

LlamaIndex

CrewAI

OpenCode

VS Code

Explore Other Toolkits

Supabase

Codeinterpreter

GitHub

Ably

Frequently asked questions

What are the differences in Tool Router MCP and Render MCP?+

Can I use Tool Router MCP with Vercel AI SDK v6?+

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

How safe is my data with Composio Tool Router?+

Start with Render.It takes 30 seconds.

Teams ship real agents on Composio