Monday, September 29, 2025

Mastering Advanced Search Queries with GraphQL in Sitecore XM Cloud - Part 3

Hi Sitecore folks!,

As your Sitecore content ecosystem evolves, the need for advanced and flexible search queries becomes paramount. Simple GraphQL queries are great for small datasets, but as the content grows and becomes more complex, so too must your queries. This article explores advanced search querying techniques, pagination, and real-world examples that you can implement in Sitecore XM Cloud to optimize content discovery and boost user experience.

Why Advanced Search Queries Matter

When working with Sitecore, especially in large-scale projects, simple queries quickly hit their limits. Advanced querying is essential for handling:

  • Multiple Conditions: Using logical operators like AND/OR for more granular control.
  • Exclusion Filters: Omitting certain results based on specific criteria.
  • Sorting and Pagination: Managing large datasets for better performance and usability.
  • Filtering on Complex or Nested Fields: Targeting multi-value or deeply nested fields.

GraphQL offers the flexibility needed to tackle these challenges efficiently, enabling developers to create precise, high-performing queries that meet both functional and performance requirements.

Tips for Writing Efficient GraphQL Queries

To get the most out of your GraphQL queries in Sitecore, consider the following best practices:

  1. Use Logical Operators (AND/OR/NEQ): Combine conditions effectively for highly specific filtering.
  2. Implement Pagination: Always paginate large result sets to avoid unnecessary data loading and to improve user experience.
  3. Sort Results for Better UX: Sort results based on fields like date or relevance to enhance how users interact with your data.
  4. Test Queries Before Integration: Use tools like GraphQL Playground to test and refine your queries, ensuring they work as expected before going live.

Common Comparison Operators

Understanding how and when to use comparison operators is key to building effective queries. Here’s a quick reference:

Operator Meaning Example Use Case

    EQ Equal to Department = "Engineering"

    NEQ Not equal to Status != "Inactive" 

    GT Greater than HireDate > "2022-01-01"

    LT Less than Salary < 50000 

    GTE Greater or equal Experience >= 5 

    LTE Less or equal Age <= 30

    IN In a list Department IN ("Engineering", "Marketing")

Practical Query Examples

Let’s explore some advanced query examples that leverage these techniques:

1. Filtering by Path, Template ID, and User Name with Pagination

In this example, we query for filtered items based on path, template ID, and user name, with pagination for improved performance.

query FilteredItemsResult(
$pageSize: Int = 10
$after: String
$rootItem: String!
$filterValue: String!
$templateId: String!
) {
ExpertData: search(
where: {
AND: [
{ name: "_path", value: $rootItem, operator: CONTAINS }
{ name: "_templates", value: $templateId, operator: EQ }
{ name: "UserName", value: $filterValue, operator: CONTAINS }
]
}
first: $pageSize
after: $after
) {
pageInfo {
endCursor
hasNext
}
results {
name
id
UserName: field(name: "UserName") { value }
}
}
}

Key Points:

  • AND Grouping: All conditions must be met.
  • Cursor-Based Pagination: Handles large datasets efficiently.

2. Advanced Event Query: Multi-Criteria Filtering

Here we combine OR filters within an AND block to find events based on location, available seats, sponsorship status, and rating. We also exclude events tagged as “Internal” or organized by “Test Org”.

query {
search(
where: {
AND: [
{ name: "_templates", value: "Event", operator: EQ }
{ name: "Status", value: "Published", operator: EQ }
{ name: "StartDate", value: "2025-01-01", operator: GTE }
{ name: "EndDate", value: "2025-12-31", operator: LTE }
{
OR: [
{ name: "City", value: "London", operator: EQ }
{ name: "City", value: "Berlin", operator: EQ }
]
}
{ name: "SeatsAvailable", value: "1", operator: GTE }
{ name: "IsVirtual", value: "false", operator: EQ }
{
OR: [
{ name: "IsSponsored", value: "true", operator: EQ }
{ name: "Rating", value: "4.5", operator: GT }
]
}
{ name: "Tags", value: "Internal", operator: NEQ }
{ name: "Organizer", value: "Test Org", operator: NEQ }
]
}
orderBy: [
{ fieldName: "StartDate", direction: ASC }
{ fieldName: "Rating", direction: DESC }
]
first: 10
) {
total
results {
items {
id
name
fields {
Title { value }
City { value }
StartDate { value }
SeatsAvailable { value }
IsVirtual { value }
IsSponsored { value }
Rating { value }
Tags { value }
Organizer { value }
}
}
pageInfo { endCursor hasNextPage }
}
}
}

3. Combining Filters for Tags and Authors

This query finds articles or news posts tagged with specific labels and authored by designated individuals, all sorted by the most recent publish date.

query {
search(
where: {
AND: [
{
OR: [
{ name: "Tags", value: "News", operator: CONTAINS }
{ name: "Tags", value: "Article", operator: CONTAINS }
]
}
{
OR: [
{ name: "Author", value: "Alice", operator: EQ }
{ name: "Author", value: "Bob", operator: EQ }
]
}
]
}
orderBy: [{ fieldName: "PublishDate", direction: DESC }]
first: 6
) {
total
results {
items {
id
name
fields {
Title { value }
Author { value }
Tags { value }
}
}
pageInfo { endCursor hasNextPage }
}
}
}

Key Points:

  • Nested OR within AND: Complex filtering allows for a flexible and tailored query.
  • Ordering by Date: Ensures the most recent articles appear first.

4. Filtering by Values Greater Than a Specified Amount

This query filters employees by department, hire date, and template, returning a list of employees hired after January 1, 2022, from either the Engineering or Marketing department.

query {
search(
where: {
AND: [
{ name: "_templates", value: "Employee", operator: EQ }
{ name: "Department", value: "Engineering;Marketing", operator: IN }
{ name: "HireDate", value: "2022-01-01", operator: GT }
]
}
orderBy: [
{ fieldName: "Department", direction: ASC }
{ fieldName: "HireDate", direction: DESC }
]
first: 12
) {
total
results {
items {
id
name
fields {
FirstName { value }
LastName { value }
Department { value }
HireDate { value }
Manager {
value
}
}
}
pageInfo { endCursor hasNextPage }
}
}
}

Conclusion

Advanced GraphQL queries provide Sitecore developers with the flexibility to handle complex search scenarios, enabling personalized content discovery and more efficient content management. By mastering pagination, logical operators, and filters, you can create powerful, scalable solutions that enhance user experience while improving performance.

I hope you enjoy this Sitecore blog. Stay tuned for more Sitecore related articles.

Till that happy Sitecoring :)

Please leave your comments or share this article if it’s useful for you.

Thursday, September 25, 2025

Unlocking the Power of GraphQL in Sitecore: A Practical Guide to Queries, Mutations, and Fragments – Part 2

Hi Sitecore folks!,
Welcome back, fellow developers! In the previous post of our GraphQL series, we dived into the basics of querying for component data in Sitecore. If you missed it, be sure to check out [Unlocking the Power of GraphQL in Sitecore: A Guide to Useful Queries – Part 1].

In this second installment, we're going to take a deeper dive into some of the more advanced features of GraphQL: mutations, fragments, and some common queries. These powerful tools allow you to extend your GraphQL usage in Sitecore, making your development work more efficient and dynamic.

We'll walk through how to harness these features, explore real-life examples, and explain how they can streamline your content management workflows. Whether you’re new to GraphQL or a seasoned pro looking to sharpen your skills, this guide will provide you with the essentials to elevate your GraphQL game.

GraphQL Mutations: Modifying Data on the Server

GraphQL isn't just a tool for reading data—it also allows you to modify data via mutations. In Sitecore, mutations empower you to create, update, or delete items, templates, media, and more directly through GraphQL queries.

Unlike REST, which typically uses GET requests to retrieve data, GraphQL uses mutations to make changes to data. This distinction ensures that your data-modifying operations are organized and explicit, reducing the potential for confusion or errors.

Create Data with Mutations

Let's start by exploring a mutation for creating new items. This is useful when you're working with content that's frequently updated or needs to be programmatically generated. Here’s an example mutation for creating a new item in Sitecore:

mutation CreateItem { createItem( name: "Created MutationsItem" template: "{4330C04F-5CAA-4E93-A2B2-634900395E51}" parent: "{C081F940-3F38-4E10-8F43-B80AA63BC1BA}" language: "en" fields: [ { name: "title", value: "New Item Created with Mutations" } { name: "subtitle", value: "This is a new Sitecore item created using mutations." } ] ) { path id } }

This mutation will create a new item with a specific template, assign it to a parent item, and populate its fields (e.g., title and subtitle). The result will return the path and ID of the newly created item.

Update Data with Mutations

Next, let’s look at a mutation for updating an existing item. For example, if you need to update an item's title and subtitle, the mutation would look like this:

mutation UpdateItem { updateItem( path: "/sitecore/content/Home/MySampleProject/MutationsItem/CreatedMutationsItem" language: "en" version: 1 fields: [ { name: "title", value: "Updated Item Title" } { name: "subtitle", value: "Updated subtitle content for the item." } ] ) { title { value } subtitle { value } } }

This mutation targets a specific item and updates its fields with the new values. The query also returns the updated title and subtitle fields.

Delete Data with Mutations

Mutations aren't just for creating and updating—they’re also powerful for deleting content. Here's an example of a mutation that deletes an item:

mutation DeleteItem { deleteItem( path: "/sitecore/content/Home/MySampleProject/MutationsItem/CreatedMutationsItem" ) }

Once executed, the specified item is removed from Sitecore’s content tree.

Fragments: Modularizing Queries for Reusability

As your queries become more complex, you may notice a lot of repetition in your field selections. This is where fragments come into play. A fragment allows you to define a set of fields once and reuse them across multiple queries. This makes your queries more modular, cleaner, and easier to maintain.

In Sitecore, you might be dealing with nested content types, so creating reusable fragments for fields like title and subtitle is incredibly helpful.

Here's an example where we define two fragments: RelatedItems and SubRelatedItems. Each fragment specifies the fields we need for those content types:

fragment RelatedItems on RelatedItems { title { value } subtitle { value } } fragment SubRelatedItems on SubRelatedItems { title { value } subtitle { value } }

Now, you can use these fragments in your main query to fetch content in a cleaner, more efficient way:

query ContentCardQuery($datasource: String!) { datasource: item(path: $datasource, language: "en") { name newsItems: children( includeTemplateIDs: ["{B5D116DE-BFE8-4A06-A3FE-90C84320ECCB}"] ) { name ...RelatedItems } blogItems: children( includeTemplateIDs: ["{02CDBE64-254B-424B-90C3-E74FDBA02572}"] ) { name ...SubRelatedItems } } }

By using inline fragment spreads (...RelatedItems and ...SubRelatedItems), this query is now much cleaner and more maintainable. The fragments handle the repetitive fields for you, and you only need to call them where necessary.

Fetching and Organizing Data Efficiently

GraphQL shines when it comes to fetching specific data. You can retrieve exactly what you need, reducing unnecessary requests and optimizing your application. Here’s an example where we query multiple data sources under a parent item, and we fetch only the required fields for news and blog items:

query ContentCardQuery($datasource: String!) { datasource: item(path: $datasource, language: "en") { name newsItems: children( includeTemplateIDs: ["{B5D116DE-BFE8-4A06-A3FE-90C84320ECCB}"] ) { name ... on RelatedItems { title { value } subtitle { value } } } blogItems: children( includeTemplateIDs: ["{02CDBE64-254B-424B-90C3-E74FDBA02572}"] ) { name ... on SubRelatedItems { title { value } subtitle { value } } } } }

In this query, we use child item queries to pull news and blog items based on their specific templates. We then use fragments to ensure we fetch only the required fields for each item.

Conclusion: GraphQL’s Full Potential in Sitecore

GraphQL in Sitecore isn’t just a powerful tool for reading data; it offers a comprehensive way to manage and interact with content. By leveraging mutations for data creation, updates, and deletions, along with fragments for cleaner, reusable queries, you can optimize your Sitecore applications and workflows.

In this part of the series, we've covered the essential techniques for handling mutations and fragments, but we’re just scratching the surface. Stay tuned for Part 3, where we’ll dive into complex queries, variables, and directives—all the advanced tools you’ll need to become a GraphQL pro in Sitecore.

Until then, get hands-on with what we've covered, and experiment with mutations and fragments in your own projects. The more you practice, the easier it will get!

I hope you enjoy this Sitecore blog. Stay tuned for more Sitecore related articles.

Till that happy Sitecoring :)

Please leave your comments or share this article if it’s useful for you.

Thursday, September 18, 2025

Mastering GraphQL Queries in Sitecore: A Developer's Practical Playbook - Part 1

Hi All,

In my Previous blog (Supercharging Sitecore with GraphQL: A Developer’s Guide) we started on GraphQL step by step instructions on how to configure and utilize the Sitecore GraphQL API on your local machine.

As developers, we've all been there. You have the power of GraphQL at your fingertips, but finding the right query pattern for your specific use case feels like searching for a needle in a digital haystack. That's exactly why this comprehensive guide exists – to be your go-to reference when you need to craft the perfect GraphQL query for Sitecore.

Setting the Stage: Understanding Your Content Structure

Before diving into queries, let's establish the foundation. Imagine you're working on an enterprise website with the following content structure:

/sitecore/content/Home/MySampleProject/Home/
├── About ├── Services ├── News └── Contact

Each of these items has specific templates with fields like:

  • About Template: Title, Subtitle, Description, Image, Date, IsTrue
  • Services Template: ServiceName, ServiceDescription, Icon, Features (Multilist)
  • News Template: Headline, Summary, Author, PublishDate, RelatedArticles (Treelist)

This realistic structure will ground all our examples in practical, real-world scenarios.

The Essential Query Patterns Every Sitecore Developer Needs

1. The Foundation Query: Getting All Field Data

Real-world scenario: You're debugging a component and need to see all available field data for an item.

query InspectAllFields($contextItem: String!) {
  item(path: $contextItem) {
    fields {
      name
      value
    }
  }
}

Query Variables:

{
  "contextItem": "/sitecore/content/Home/MySampleProject/Home/About"
}

Why this matters: This is your debugging lifeline. When a component isn't displaying correctly, this query shows you exactly what data is available and how it's structured.

2. The Content Retrieval Pattern: Getting Specific Item Data

Real-world scenario: You're building a hero component that needs specific fields from a content item.

query HeroComponentData {
  item(path: "/sitecore/content/Home/MySampleProject/Home/About") {
id name template { name } subTitle: field(name: "SubTitle") { value } description: field(name: "Description") { value } } }

Developer insight: Notice how we're using aliases (subTitle, description) to make the response more readable and match our frontend component props.

3. The Template Filter Pattern: Type-Safe Content Querying

Real-world scenario: You have a mixed content area, but only want to display specific item types.

query FilteredChildrenByTemplate($contextItem: String!) {
  item(path: $contextItem) {
    children {
      ... on About {
        id
        name
        title: field(name: "Title") {
          value
        }
        subtitle: field(name: "Subtitle") {
          value
        }
      }
      ... on Services {
        id
        name
        serviceName: field(name: "ServiceName") {
          value
        }
        serviceDescription: field(name: "ServiceDescription") {
          value
        }
      }
    }
  }
}

Pro tip: This pattern is incredibly powerful for building dynamic listing components where different item types need different field mappings.

4. The Common Fields Pattern: Flexible Content Components

Real-world scenario: You're building a card component that can display different content types but needs consistent field access.

query FlexibleContentCard($datasource: String!) {
  datasource: item(path: $datasource, language: "en") {
    id
    name
    url
    ... on About {
      title {
        value
      }
      subtitle {
        value
      }
      image {
        alt
        src
      }
      link {
        url
      }
      date {
        value
      }
      isTrue {
        value
      }
    }
    ... on News {
      headline: title {
        value
      }
      summary: subtitle {
        value
      }
      publishDate: date {
        value
      }
      author {
        value
      }
    }
  }
}

Developer insight: This pattern allows one component to handle multiple content types gracefully, reducing code duplication.

5. The Relationship Query Pattern: Handling Multilist and Treelist Fields

Real-world scenario: You're building a services page where each service has related case studies or features.

Approach 1: Direct Field Access

query ServiceWithRelatedItems($datasource: String!) {
  datasource: item(path: $datasource, language: "en") {
    id
    name
    ... on Services {
      serviceName: title {
        value
      }
      serviceDescription: subtitle {
        value
      }
      relatedFeatures: multiListItems {
        id
        name
        targetItems {
          id
          name
          path
          ... on Feature {
            featureName: title {
              value
            }
            featureDescription: description {
              value
            }
            icon {
              src
              alt
            }
          }
        }
      }
    }
  }
}

Approach 2: Search-Based Access

query ServiceFeaturesViaSearch {
  search(
    fieldsEqual: [
      {
        name: "_fullpath"
        value: "/sitecore/content/Home/MySampleProject/Home/Services"
} ] keyword: "" ) { results { items { item { ... on Services { serviceName: title { value } relatedFeatures: multiListItems { value name targetItems { id name ... on Feature { featureName: title { value } description { value } } } } } } } } } }

When to use which approach: Use Approach 1 when you know the exact item path. Use Approach 2 when you need to find items dynamically or apply additional search criteria.

6. The DropLink Pattern: Single Reference Fields

Real-world scenario: Your news articles reference a single author item, and you need author details.

query NewsWithAuthor($datasource: String!) {
  datasource: item(path: $datasource, language: "en") {
    id
    name
    ... on News {
      headline: title {
        value
      }
      summary {
        value
      }
      authorReference: dropLinkItem {
        id
        name
        targetItem {
          id
          name
          ... on Author {
            fullName: displayName {
              value
            }
            bio {
              value
            }
            profileImage {
              src
              alt
            }
          }
        }
      }
    }
  }
}

7. The Alias Power Pattern: Clean, Component-Ready Data

Real-world scenario: Your frontend team needs field names that match their component props exactly.

query ComponentReadyData($contextItem: String!) {
  componentData: item(path: $contextItem) {
    componentId: id
    ... on About {
      heading: title {
        value
      }
      subheading: subtitle {
        value
      }
      bodyText: description {
        value
      }
      ctaLink: link {
        url
        target
      }
    }
  }
}

Developer benefit: This eliminates the need for field mapping in your frontend code, making components cleaner and more maintainable.

8. The Hierarchical Data Pattern: Multi-Level Navigation

Real-world scenario: You're building a navigation component that needs to show page hierarchies.

query NavigationStructure {
  item(path: "/sitecore/content/Home/MySampleProject/Home") {
children { name id url template { name } ... on NavigationItem { navigationTitle: title { value } showInNavigation { value } } children { name id url template { name } ... on NavigationItem { navigationTitle: title { value } showInNavigation { value } } # Third level if needed children { name id url ... on NavigationItem { navigationTitle: title { value } } } } } } }

9. The Template-Only Fields Pattern: Clean Data Filtering

Real-world scenario: You want to avoid system fields and only get template-defined fields for a cleaner component interface.

query CleanTemplateFields($contextItem: String!) {
  item(path: $contextItem) {
    fields(ownFields: true) {
      id
      name
      value
      type
    }
    template {
      name
      fields {
        name
        type
      }
    }
  }
}

Why this matters: This prevents your components from accidentally depending on Sitecore system fields, making them more portable and maintainable.

10. The Search Mastery Patterns: Finding Content Dynamically

Pattern A: Exact Field Matching

Real-world scenario: Finding all blog posts by a specific author.

query BlogPostsByAuthor {
  search(
    fieldsEqual: [
      {
        name: "author"
        value: "John Smith"
      }
      {
        name: "_template"
        value: "BlogPost"
      }
    ]
    rootItem: "/sitecore/content/Home/MySampleProject/Home/Blog"
) { results { totalCount items { item { id name path url ... on BlogPost { title { value } publishDate { value } summary { value } author { value } } } } } } }

Pattern B: Keyword Search

Real-world scenario: Building a site search feature.

query SiteSearch($searchTerm: String!, $searchRoot: String!) {
  search(
    keyword: $searchTerm
    rootItem: $searchRoot
  ) {
    results {
      totalCount
      items {
        item {
          id
          name
          path
          url
          template {
            name
          }
          # Get title field regardless of template
          title: field(name: "Title") {
            value
          }
          # Get description field regardless of template
          description: field(name: "Description") {
            value
          }
        }
      }
    }
  }
}

Query Variables:

{
  "searchTerm": "GraphQL",
  "searchRoot": "/sitecore/content/Home/MySampleProject/Home"
}

Pattern C: Complex Field-Based Search

Real-world scenario: Finding products within a specific category and price range.

query ProductSearch {
  search(
    fieldsEqual: [
      {
        name: "Category"
        value: "Electronics"
      }
      {
        name: "InStock"
        value: "1"
      }
    ]
    rootItem: "/sitecore/content/Home/MySampleProject/Home/Products"
) { results { totalCount items { item { id name path url ... on Product { productName: title { value } price { value } category { value } inStock { value } productImage: image { src alt } } } } } } }

Advanced Patterns for Complex Scenarios

Error-Handling Query Pattern

Real-world scenario: You need to ensure your queries gracefully handle missing content.

query SafeContentQuery($contextItem: String!) {
  item(path: $contextItem) {
    id
    name
    template {
      name
    }
    ... on About {
      title {
        value
        ... on TextField {
          value
        }
      }
      # Fallback for missing fields
      subtitle {
        value
      } @skip(if: false)
    }
  }
}

Multi-Language Content Pattern

Real-world scenario: Building a multilingual site with language-specific content.

query MultiLanguageContent($itemPath: String!, $language: String!) {
  item(path: $itemPath, language: $language) {
    id
    name
    language
    ... on About {
      title {
        value
      }
      subtitle {
        value
      }
    }
  }
  
  # Get versions in other languages
  allLanguages: item(path: $itemPath) {
    versions {
      language
      version
    }
  }
}

Performance Optimization Tips from the Trenches

1. Query Only What You Need

# ❌ Avoid: Over-fetching
query BadExample {
  item(path: "/sitecore/content/Home/MySampleProject/Home") {
fields { name value } children { fields { name value } } } } # ✅ Better: Specific field requests query GoodExample { item(path: "/sitecore/content/Home/MySampleProject/Home") {
title { value } description { value } } }

2. Use Fragments for Reusable Patterns

fragment BasicItemInfo on Item {
  id
  name
  path
  url
}

fragment ContentFields on About {
  title {
    value
  }
  subtitle {
    value
  }
  image {
    src
    alt
  }
}

query OptimizedQuery($contextItem: String!) {
  item(path: $contextItem) {
    ...BasicItemInfo
    ...ContentFields
  }
}

Troubleshooting Common Issues

Problem: "Field not found" Errors

Solution: Always check your template inheritance and field names in Sitecore. Use the field inspection query first.

Problem: Empty Results from Search Queries

Solution: Verify your search indexes are up to date and check field value formatting (especially for boolean and date fields).

Problem: Performance Issues with Deep Hierarchies

Solution: Limit nesting levels and use search queries instead of deep children traversals when possible.

Building Your GraphQL Query Library

As you work with these patterns, consider building a team library of commonly used queries. Here's a suggested structure:

/graphql-queries/
├── /components/
│   ├── hero-queries.graphql
│   ├── navigation-queries.graphql
│   └── listing-queries.graphql
├── /search/
│   ├── content-search.graphql
│   └── product-search.graphql
└── /utils/
    ├── field-inspection.graphql
    └── debug-queries.graphql

The Path Forward: From Queries to Solutions

Understanding these query patterns is just the beginning. The real power comes from combining them creatively to solve specific business challenges. Whether you're building a dynamic product catalog, a complex news portal, or an interactive corporate website, these patterns provide the building blocks for success.

Remember, GraphQL in Sitecore isn't just about fetching data – it's about empowering your development team to build more maintainable, performant, and scalable digital experiences. Every query you craft is an investment in your application's future flexibility and your team's productivity.

Your Next Steps

  1. Start with the basics: Master the field inspection and content retrieval patterns
  2. Build incrementally: Add complexity gradually as your comfort level increases
  3. Document your discoveries: Keep notes on query patterns that work well for your specific use cases
  4. Share with your team: Create a shared knowledge base of successful query patterns
  5. Performance test: Always validate that your queries perform well with realistic data volumes

The journey to GraphQL mastery in Sitecore is iterative. Each query you write, each pattern you discover, and each problem you solve adds to your expertise. Your future self – and your entire development team – will thank you for building this foundation of knowledge and practical experience.


Ready to dive deeper? The Sitecore and GraphQL communities are incredibly supportive. Don't hesitate to share your own query discoveries and learn from others who are solving similar challenges.

I hope you enjoy this Sitecore blog. Stay tuned for more Sitecore related articles.

Till that happy Sitecoring :)

Please leave your comments or share this article if it’s useful for you.

Monday, September 8, 2025

Supercharging Sitecore with GraphQL: A Developer’s Guide

Introduction

In the dynamic world of web development, efficiency and performance are paramount. One powerful way to achieve both is by integrating GraphQL with Sitecore, a leading enterprise content management system. While GraphQL isn’t new to Sitecore, the advent of Sitecore JavaScript Services (JSS) has made its implementation smoother and more accessible than ever.

This guide walks you through the process of setting up GraphQL in Sitecore, focusing on how to craft effective queries to retrieve content. Whether you're building a new solution or enhancing an existing one, this integration can be a game-changer.


Why GraphQL with Sitecore?

Integrating GraphQL into Sitecore offers a host of benefits:

  • Enhanced Flexibility: Fetch only the data you need—no more, no less.
  • Streamlined Development: Decouple frontend and backend workflows for faster iteration.
  • Improved Performance: Reduce payload sizes and speed up response times.
  • Modern Frontend Compatibility: GraphQL’s schema-based approach aligns perfectly with frameworks like React, Vue.js, and Angular.

Getting Started: Installing JSS and GraphQL

To begin, you’ll need the correct JSS server component package for your Sitecore version. Once identified:

Step 1: Install the JSS Package

  • Open Sitecore in your browser.
  • Navigate to: Desktop → Development Tools → Installation Wizard.
  • Upload and install the JSS package.

This installation will add several components to your Sitecore instance:

  • Configuration files under App_Config (including LayoutService and GraphQL configs).
  • DLLs in the bin folder.
  • JssApp.cshtml view file.
  • Sitecore templates under Foundation and System.

Step 2: Configure GraphQL

After installation:

  1. Go to App_Config\Services.GraphQL.
  2. Rename the file Sitecore.Services.GraphQL.Content.Master.config.example to Sitecore.Services.GraphQL.Content.Master.config.

Step 3: Add and Configure API Key

To query GraphQL via API:

  1. Switch to the Core database.
  2. Navigate to /sitecore/system/Settings/Services/API Keys.
  3. Right-click and insert a new API Key item.

Enable API Key Authentication

Edit the file:
App_Config\Sitecore\Services.GraphQL\Sitecore.Services.GraphQL.config

In the <security> section, enable API Key authentication.


Step 4: Access the GraphQL Browser

Once everything is set up, you can test your queries using the Sitecore GraphQL Browser:

  • URL format:
    https://your-domain/sitecore/api/graph/items/master/ui

If you encounter an “Authentication required” error:

Fix: Add Site-Neutral Path

  1. Open:
    App_Config\Sitecore\Owin.Authentication\Sitecore.Owin.Authentication.config
  2. Locate the <siteNeutralPaths> node.
  3. Add:
    /sitecore/api/graph/items/

Save the file and retry accessing the GraphQL browser.


Step 5: Run Your First Query

Here’s a sample GraphQL query to fetch child items of a context item:

query GQLQuerySamples($contextItem: String!) {
  item(path: $contextItem) {
    children {
      id
      name
    }
  }
}

Important Notes:

  • In the Query Variables section, pass the contextItem path.
  • In the HTTP Headers, include your API Key.

Conclusion

Integrating GraphQL with Sitecore empowers developers to build faster, leaner, and more scalable applications. With precise data fetching, improved performance, and seamless frontend integration, GraphQL is a natural fit for modern Sitecore solutions.

Whether you're a seasoned Sitecore developer or just getting started, embracing GraphQL can elevate your development workflow and deliver richer digital experiences.

I hope you enjoy this Sitecore blog. Stay tuned for more Sitecore related articles.

Till that happy Sitecoring :)

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