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Connect your Okendo MCP Server to ChatGPT and Claude

Use the Okendo Model Context Protocol (MCP) Server to securely connect your public reviews data to AI tools like ChatGPT and Claude.

Written by James Fletcher

This integration allows you to query your reviews using natural language, uncover insights, and power AI-driven shopper experiences.

In this article, you will learn about:

  • What the Okendo MCP Server does

  • What you need before connecting

  • How to retrieve your MCP URL

  • How to connect the MCP Server to ChatGPT

  • How to connect the MCP Server to Claude

  • The available Okendo MCP tools

  • Example use cases for merchants and partners

  • Best practices when using AI with your review data

  • Frequently asked questions

Understanding the Okendo MCP Server

The Okendo MCP Server lets you connect your public Reviews data to AI models like ChatGPT and Claude.
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This connection enables new ways to work with customer feedback and drive insights for your business.
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You can use it to:

  • Summarize sentiment and themes across your product reviews.

  • Generate authentic marketing content using real customer voices.

  • Identify product opportunities based on positive and negative feedback.

  • Power AI tools and shopper experiences that use real customer insights.

The Okendo MCP Server integrates seamlessly with ChatGPT and Claude, and enables you to dig deeper for internal analysis, marketing workflows, or partner-built shopper experiences.

Prerequisites

Before you get started, ensure you have:

  • An active Okendo Reviews plan with review data from your customers.

  • Admin access to your Okendo dashboard.

  • Access to an AI tool that supports MCP connections (e.g. ChatGPT or Claude).

Retrieve your MCP URL

  1. Open the Integrations page in Okendo, by selecting Settings > Integrations

  2. Select the pencil icon next to the Okendo section within the AI & MCP category

  3. Toggle the "Enable MCP Server" to allow the integration.

  4. Select Copy next to your MCP URL

  5. Then press "Save" to confirm the changes.

Connecting via ChatGPT

Enabling developer mode

  1. Enable developer mode by going to Settings → Security and login → Developer mode

Connecting to Okendo MCP Server

  1. Navigate to Plugins from the sidebar, and select the plus (+) button

  2. Configure the following fields on the New Plugin dialog:

    • Name: Okendo

    • MCP Server URL: https://mcp.okendo.io/stores/{USER_ID}

    • Authentication: No Auth

  3. Check I understand and want to continue and then select Create

  4. Select Connect to finalise the connection to the Okendo MCP Server

Installing the Shopify plugin

  1. Navigate to Plugins from the sidebar, and search for the Shopify plugin

  2. Select Install plugin and follow the prompts

Connecting via Claude

💡 Claude Free plans only allow adding 1 custom connector.

Connecting to Okendo MCP Server

  1. Navigate to Settings → Customize → Connectors.

  2. Select Add → Add custom connector

  3. Configure the following fields on the Add custom connector dialog:

    • Name: Okendo

    • Remote MCP server URL: https://mcp.okendo.io/stores/{USER_ID}

  4. Select Add and then Connect to finish adding your connector

  5. Confirm that the MCP tool has been successfully connected by selecting the plus (+) button and then Connectors under the chat bar

Connecting the Shopify connector

  1. Navigate to Settings → Connectors → Directory, and search for the Shopify connector

  2. Select Connect to Claude and follow the prompts

Available Okendo MCP tools

reviews_aggregate

Retrieves product review aggregate data including total reviews, rating distribution, average ratings, recommendation percentage, and attribute data for Shopify products. Can be retrieved for a specific product, or for the entire store.

reviews_search

Lists product reviews matching specified filter criteria with support for text search, rating filters, date ranges, and pagination.

questions_list

Lists published and approved product questions and their associated answers for a given Shopify product. If the product belongs to a group (collection), questions and answers for that group will also be retrieved. Supports sorting by most recent, oldest, or most helpful, with pagination.

Use cases for Okendo MCP Server

1. Merchandising and product development

Make data-driven product and merchandising decisions by turning review sentiment and themes into actionable insights.

How merchants can use it:

  • Ask: "What are customers saying about the fit and sizing of our new collection?"

  • Aggregate sentiment across products to identify manufacturing or quality issues early.

  • Compare new vs. legacy product sentiment to guide restocking or discontinuation.

  • Identify recurring keywords (e.g., "too small", "scratchy", "perfect fit") to feed back to design teams.

  • Detect feature requests or unmet needs that can feed into R&D.

Example queries:

  • "Summarize key complaints about our boots line."

  • "What words most commonly appear in 5-star reviews for our boots?"

2. Marketing and campaign planning

Help translate authentic customer feedback into marketing messaging and creative assets to drive acquisition and conversion.

How merchants can use it:

  • Surface top themes or sentiments to shape messaging, campaigns, and UGC use.

  • Identify emotional drivers of purchase decisions (e.g., "perfect for travel", "eco-friendly").

  • Pull real quotes and aggregate sentiment for landing pages, ad copy, or emails.

  • Analyze which features or benefits customers emphasize most to optimize positioning.

Example queries:

  • "Summarize what customers love most about our 'Chelsea Rise Vintage Tan'."

  • "Which products have the most positive sentiment around 'sustainability'?"

  • "Show me reviews that talk about this being a good 'gift'."

  • "Put together a list of customer quotes from my 5-star reviews that I can use in my marketing copy."

3. Customer support and CX

Use review data to identify, reduce, and pre-empt customer pain points, improving satisfaction and lowering support overhead.

How merchants can use it:

  • Identify recurring issues that drive support volume ("delayed shipping", "wrong size", "poor packaging").

  • Understand what customers praise or complain about most, then proactively address it in FAQs or chatbots.

  • Track changes in sentiment over time after product changes or campaigns.

Example queries:

  • "What themes appear most often in 1–2 star reviews this month?"

  • "Which products receive the most mentions of 'customer service'?"

  • "Summarize top pain points customers mention about 'shipping'."

4. Loyalty and retention

Use reviews as a retention layer to identify advocates, at-risk customers, and engagement opportunities within the Loyalty and/or Memberships ecosystem.

How merchants can use it:

  • Identify promoters and advocates from reviews to invite into loyalty tiers or memberships.

  • Analyze churn signals from negative reviews that mention "cancelled", "too expensive", or "didn't work."

Example queries:

  • "Which customers mention being repeat buyers?"

  • "What are the main reasons customers say they stopped purchasing?"

5. Partners and agencies

Help provide data-backed strategic recommendations to merchants by analyzing review sentiment, trends, and themes through the MCP Server. Additionally, power conversational shopping assistants or "Store Concierge" bots using Okendo's MCP Server.

How partners use it:

  • Analyze merchant review data at scale, surfacing insights that inform brand, CX, and marketing strategy.

  • Pull Okendo review sentiment data to identify customer priorities, complaints, and trends across SKUs or collections.

  • Connect Okendo MCP Server to allow queries inside Storefront Concierge bots or custom GPTs that help shoppers discover products and make confident buying decisions using verified customer sentiment.

Example queries:

  • "Summarize the top positive and negative themes in all reviews for the last 90 days."

  • "Compare customer sentiment before and after our June product relaunch."

  • "Find reviews mentioning 'gift' or 'holiday' for products in the 'Boots' category."

  • "Show 3 customer quotes describing the fit of the 'Chelsea Rise Vintage Tan'."

Best practices

✅ Be specific in your prompts

Ask clear, targeted questions for more accurate AI responses.

✅ Filter your queries

Limit your scope by product or time range to get cleaner, more relevant insights.

⚠ Review before sharing externally

AI responses may occasionally misinterpret tone or meaning. Always verify before publishing or acting on insights.

Disclaimer

❗ Outputs generated through AI models using the Okendo MCP Server are summaries and may not always reflect exact customer statements. Always review results before public use.

Frequently asked questions

1. What is the Okendo MCP server?

The Okendo Model Context Protocol (MCP) server lets you connect your public Okendo reviews into AI tools like ChatGPT or Claude. This gives you the ability to query your customer feedback in natural language and use that data in new ways.

2. What can I do with it today?

Current use cases include:

  • Summarizing customer sentiment across products.

  • Identifying common likes and dislikes to inform promotions or product improvements.

  • Quickly generating marketing copy/snippets grounded in authentic reviews.

  • Powering AI concierge bots with trusted review data to help shoppers.

  • Much more — give it a try and see what you can learn!

3. Can shoppers use this directly on my store?

No. The initial release is merchant and partner-facing, and needs to be accessed with a subscription to ChatGPT or Claude. It's designed to help you analyze, summarize, and activate your public review data. However, developers and agencies can integrate the Okendo MCP server into concierge bots or other shopper-facing AI experiences.

4. Do I need technical skills to use MCP?

Basic setup is straightforward, but more advanced use cases (e.g., custom concierge bots, integrations into dashboards) may require developer support. You don't need any technical skills to query the data in an AI agent like ChatGPT or Claude, though.

5. How is this different from the Shopify Storefront MCP server?

Shopify's Storefront MCP server connects your live store data — like product catalog, variants, policies, and cart actions — directly into AI models such as ChatGPT or Claude. Okendo's MCP Server complements this by connecting your authentic public review data.

Together they enable richer, more accurate insights. For example, you can ask:

  • "Which products under $100 get the highest ratings for durability?"

  • "Highlight 5 products with the best customer feedback about quality, and give me language I can reuse in ad copy."

6. Can partners or agencies use this on behalf of merchants?

Yes. Agencies and technology partners can use Okendo's MCP server to build AI-powered tools and workflows that incorporate your review data, from dashboards to concierge bots.

7. Does connecting to the Okendo MCP Server open up any data or privacy issues?

No. The Okendo MCP Server can only access the review information that is publicly published on your review display. It does not have access to private customer data, email addresses, or any information not already visible on your site. The data it works with is limited to the published review text only.

8. I have multiple Shopify storefronts. Can I analyze review sentiment across all my stores at once?

Yes! You can set up each store individually by copying the MCP URL from each store's Okendo integration dashboard and creating individual MCP connectors in ChatGPT or Claude. Once configured, you can query them together by asking Claude to "show me the top sentiments from each store broken down." Alternatively, you can query each store separately if you prefer individual analysis.

9. What kind of data can I access with this integration? Can it pull my order data or average order value?

The Okendo MCP integration can only access and analyze your public review data — it searches and aggregates review information exclusively. It cannot access broader store data like order information, average order value, or other Shopify store metrics.

10. Can I use this to help draft responses to customer reviews or support tickets?

Yes! You can use ChatGPT or Claude to help craft empathetic, personalized responses. For example, you could prompt: "Pull all reviews from the last 14 days that mention [specific issue]" and then ask Claude to "provide an empathetic response that includes [your specific parameters like refund offers, solutions, etc.]."

While this can save time, we recommend personalizing AI-generated responses before sending them to maintain authenticity with your customers.

11. Can I train the AI to respond in my brand's voice or specific tone?

While you cannot train the underlying AI model (ChatGPT or Claude), you can control the tone and style through your prompts. For example, you can specify: "Write a response to this review in a professional and empathetic tone" or "Summarize these reviews in a casual, friendly voice." The AI will adapt its language based on your instructions within each prompt.

12. Can I connect other data sources like Google Analytics alongside my Okendo reviews?

Theoretically, yes! If other platforms have MCP server integrations (like Google Analytics), you could connect multiple MCP data sources and query them together in ChatGPT or Claude. This would allow you to cross-reference review data with other business metrics. However, the effectiveness will depend on how well ChatGPT or Claude can connect insights across different data sources.
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