Connect your Okendo MCP Server to ChatGPT or Claude

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 User ID
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 & Partners
Best practices when using AI with your review data

Understanding the Okendo MCP Server

The Okendo MCP Server lets you connect your public Reviews data to AI models like ChatGPT and Claude.

This connection enables new ways to work with customer feedback and drive insights for your business.

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 Plus/Pro or Claude Team/Enterprise).

Retrieve your User ID

Open the Integrations page in Okendo, by selecting Settings > Integrations
Select the pencil icon next to the Okendo section
Select Copy next to your User ID

Connect Okendo MCP Server to ChatGPT

💡Full MCP support is currently available only for ChatGPT Plus and Pro plans on the web.

Connecting to Okendo MCP Server

Enable developer mode by going to Settings → Connectors → Advanced → Developer mode
In the chat bar, select “+” → More → Developer Mode
Select Add sources → Connect more and configure the following fields:
- Name: Okendo
- MCP Server URL: https://mcp.okendo.io/stores/{USER_ID}
- Authentication: No authentication
Select I trust this application → Create

Connecting to Shopify MCP Server

Select Add sources → Connect more and configure the following fields:
- Name: Shopify
- MCP Server URL: https://{SHOP_ID}.myshopify.com/api/mcp
- Authentication: No authentication
Select I trust this application → Create

Connect Okendo MCP Server to Claude (Custom Connector)

Navigate to Settings > Connectors.
For Enterprise and Team plan Owners/Primary Owners, select Organization connectors at the top of the page
Select Add custom connector at the bottom of the page and configure the following fields:
- Name: Okendo
- Remote MCP server URL: https://mcp.okendo.io/stores/{USER_ID}
Finish configuring your connector by clicking "Add."
Confirm that the MCP tools have been discovered by clicking Search and tools under the chat bar

Connect Okendo MCP Server to Claude (via Local Bridge)

Select Settings → Developer → Edit Config

In claude_desktop_config.json, configure the following JSON:

{     "mcpServers": {       "okendo": {         "command": "npx",         "args": [           "mcp-remote",            "<https://mcp.okendo.io/stores/{USER_ID}>"         ]       },       "shopify": {         "command": "npx",         "args": [           "mcp-remote",            "https://{SHOP_ID}.myshopify.com/api/mcp"         ]       }     }   }

If you are using MAC OS, you will likely have to explicitly configure node version paths like so:

{     "mcpServers": {       "okendo": {         "command": "/Users/{USERNAME}/.nvm/versions/node/v22.18.0/bin/npx",         "args": [           "mcp-remote",            "<https://mcp.okendo.io/stores/{USER_ID}>"         ],         "env": {           "PATH": "/Users/{USERNAME}/.nvm/versions/node/v22.18.0/bin:/usr/local/bin:/usr/bin:/bin",           "NODE_PATH": "/Users/{USERNAME}/.nvm/versions/node/v22.18.0/lib/node_modules"         }       },       "shopify": {         "command": "/Users/{USERNAME}/.nvm/versions/node/v22.18.0/bin/npx",         "args": [           "mcp-remote",            "https://{SHOP_ID}.myshopify.com/api/mcp"         ],         "env": {           "PATH": "/Users/{USERNAME}/.nvm/versions/node/v22.18.0/bin:/usr/local/bin:/usr/bin:/bin",           "NODE_PATH": "/Users/{USERNAME}/.nvm/versions/node/v22.18.0/lib/node_modules"         }       }     }   }

Confirm that the MCP tools have been discovered by clicking Search and tools under the chat bar

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.

Use cases for Okendo MCP Server

1. Merchandising & 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 & 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 & 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 & 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 & 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.