# How to integrate Storerocket MCP with Codex

```json
{
  "title": "How to integrate Storerocket MCP with Codex",
  "toolkit": "Storerocket",
  "toolkit_slug": "storerocket",
  "framework": "Codex",
  "framework_slug": "codex",
  "url": "https://composio.dev/toolkits/storerocket/framework/codex",
  "markdown_url": "https://composio.dev/toolkits/storerocket/framework/codex.md",
  "updated_at": "2026-05-12T10:27:14.779Z"
}
```

## Introduction

Codex is one of the most popular coding harnesses out there. And MCP makes the experience even better. With Storerocket MCP integration, you can draft, triage, summarise emails, and much more, all without leaving the terminal or the app, whichever you prefer.

## Also integrate Storerocket with

- [OpenAI Agents SDK](https://composio.dev/toolkits/storerocket/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/storerocket/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/storerocket/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/storerocket/framework/claude-cowork)
- [OpenClaw](https://composio.dev/toolkits/storerocket/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/storerocket/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/storerocket/framework/cli)
- [Google ADK](https://composio.dev/toolkits/storerocket/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/storerocket/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/storerocket/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/storerocket/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/storerocket/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/storerocket/framework/crew-ai)

## TL;DR

### Why use Composio?
Apart from a managed and hosted MCP server, you will get:
- CodeAct: A dedicated workbench that allows GPT to write its code to handle complex tool chaining. Reduces to-and-fro with LLMs for frequent tool calling.
- Large tool responses: Handle them to minimise context rot.
- Dynamic just-in-time access to 20,000 tools across 1000+ other Apps for cross-app workflows. It loads the tools you need, so GPTs aren't overwhelmed by tools you don't need.

## Connect Storerocket to Codex

### How to install Storerocket MCP in Codex
### Run the setup command
Run this command in your terminal to add the Composio MCP server to Codex.

```bash
codex mcp add composio --url https://connect.composio.dev/mcp
```

## What is the Storerocket MCP server, and what's possible with it?

The Storerocket MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Storerocket account. It provides structured and secure access to your Storerocket user management features, so your agent can perform actions like retrieving user details, listing team members, and managing account access on your behalf.
- Retrieve current user details: Instantly fetch information about the authenticated user—great for confirming account access or displaying profile data.
- List all Storerocket users: Effortlessly pull a full list of users in your organization, including support for pagination if you have a large team.
- User management automation: Let your agent streamline workflows that require user lookups or bulk actions across your Storerocket account.
- Centralized account insights: Quickly access and review who has access to your Storerocket store locator dashboard for audits or team updates.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `STOREROCKET_GET_USERS` | Get authenticated user | Tool to retrieve the authenticated user information. Use when you need to get details about the currently authenticated user. |
| `STOREROCKET_PING` | Ping API health check | Tool to verify API availability via health check endpoint. Use when you need to check if the StoreRocket API is accessible and responding. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Storerocket MCP server provides comprehensive access to Storerocket operations through Composio. Once connected, you can perform all major Storerocket actions directly from Codex using natural language commands.

## Complete Code

None listed.

## Conclusion

### Conclusion
You've successfully integrated Storerocket with Codex using Composio's MCP server. Now you can interact with Storerocket directly from your terminal, VS Code, or the Codex App using natural language commands.
Key benefits of this setup:
- Seamless integration across CLI, VS Code, and standalone app
- Natural language commands for Storerocket operations
- Managed authentication through Composio
- Access to 20,000+ tools across 1000+ apps for cross-app workflows
- CodeAct workbench for complex tool chaining
Next steps:
- Try asking Codex to perform various Storerocket operations
- Explore cross-app workflows by connecting more toolkits
- Build automation scripts that leverage Codex's AI capabilities

## How to build Storerocket MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/storerocket/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/storerocket/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/storerocket/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/storerocket/framework/claude-cowork)
- [OpenClaw](https://composio.dev/toolkits/storerocket/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/storerocket/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/storerocket/framework/cli)
- [Google ADK](https://composio.dev/toolkits/storerocket/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/storerocket/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/storerocket/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/storerocket/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/storerocket/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/storerocket/framework/crew-ai)

## Related Toolkits

- [Addresszen](https://composio.dev/toolkits/addresszen) - Addresszen is a real-time address autocomplete and verification service. It helps capture accurate, deliverable addresses with instant suggestions and validation.
- [Asin data api](https://composio.dev/toolkits/asin_data_api) - Asin data api gives you detailed, real-time product data from Amazon, including price, rank, and reviews. Perfect for e-commerce pros and data-driven marketers who need instant marketplace insights.
- [Baselinker](https://composio.dev/toolkits/baselinker) - BaseLinker is an all-in-one e-commerce management platform connecting stores, marketplaces, carriers, and more. It streamlines order processing, inventory control, and automates your sales operations.
- [Bestbuy](https://composio.dev/toolkits/bestbuy) - Best Buy is a leading retailer offering APIs for product, store, and recommendation data. Instantly access up-to-date retail insights for smarter shopping and decision-making.
- [Btcpay server](https://composio.dev/toolkits/btcpay_server) - BTCPay Server is a free, open-source, self-hosted Bitcoin payment processor. It lets merchants accept Bitcoin payments directly, cutting out middlemen and boosting privacy.
- [Cdr platform](https://composio.dev/toolkits/cdr_platform) - Cdr platform is an API for purchasing carbon dioxide removal services. It enables businesses to offset emissions by accessing verified carbon removal projects.
- [Cloudcart](https://composio.dev/toolkits/cloudcart) - CloudCart is an e-commerce platform for building and managing online stores. It helps businesses streamline product listings, orders, and customer engagement.
- [Countdown api](https://composio.dev/toolkits/countdown_api) - Countdown API gives you real-time, structured eBay product data, reviews, and seller feedback. Perfect for powering price monitoring, product research, or marketplace analytics workflows.
- [Dpd2](https://composio.dev/toolkits/dpd2) - Dpd2 is a robust email management platform for handling, sorting, and automating email workflows. Streamline your communications and boost productivity with advanced sorting, labeling, and response tools.
- [Finerworks](https://composio.dev/toolkits/finerworks) - FinerWorks is an online platform for fine art and photo printing services. Artists and photographers use it to order custom prints and manage print inventory efficiently.
- [Fingertip](https://composio.dev/toolkits/fingertip) - Fingertip is a business management platform for selling, booking, and customer engagement—all from a single link. It helps businesses streamline operations and connect with customers across social channels.
- [Fraudlabs pro](https://composio.dev/toolkits/fraudlabs_pro) - FraudLabs Pro is an online payment fraud detection service for e-commerce and merchants. It helps minimize chargebacks and revenue loss by detecting and preventing fraudulent transactions.
- [Gift up](https://composio.dev/toolkits/gift_up) - Gift Up! is a digital platform for selling, managing, and redeeming gift cards online. It streamlines promotions and gift card transactions for businesses and their customers.
- [Goody](https://composio.dev/toolkits/goody) - Goody is a gifting platform that lets users send gifts and physical products without handling logistics. It streamlines gifting by managing delivery, fulfillment, and recipient experience.
- [Gumroad](https://composio.dev/toolkits/gumroad) - Gumroad is a platform for selling digital products, physical goods, and memberships with a simple checkout and marketing tools. It streamlines creator payouts and helps you grow your audience effortlessly.
- [Instacart](https://composio.dev/toolkits/instacart) - Instacart is an online grocery delivery and pickup service platform. It lets you discover local retailers and create shoppable lists and recipes with ease.
- [Junglescout](https://composio.dev/toolkits/junglescout) - Junglescout is an Amazon product research and analytics platform for sellers. It delivers sales estimates, competitive insights, and optimization tools to boost your Amazon business.
- [Ko fi](https://composio.dev/toolkits/ko_fi) - Ko-fi is a platform that lets creators receive donations, memberships, and sales from fans. It helps creators monetize their work and grow their audience with minimal friction.
- [Lemon squeezy](https://composio.dev/toolkits/lemon_squeezy) - Lemon Squeezy is a payments and subscription platform built for software companies. It makes managing payments, taxes, and customer subscriptions effortless.
- [Loyverse](https://composio.dev/toolkits/loyverse) - Loyverse is a point-of-sale (POS) platform for small businesses, offering tools for sales, inventory, and customer loyalty. It helps streamline retail operations and boost customer engagement.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Storerocket MCP?

With a standalone Storerocket MCP server, the agents and LLMs can only access a fixed set of Storerocket tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Storerocket and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Codex?

Yes, you can. Codex 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 Storerocket tools.

### Can I manage the permissions and scopes for Storerocket while using Tool Router?

Yes, absolutely. You can configure which Storerocket 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.

### How safe is my data with Composio Tool Router?

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 Storerocket data and credentials are handled as safely as possible.

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