{"id":28420,"date":"2026-04-14T13:23:20","date_gmt":"2026-04-14T13:23:20","guid":{"rendered":"https:\/\/refiner.io\/docs\/?post_type=knowledgebase&#038;p=28420"},"modified":"2026-04-14T13:48:21","modified_gmt":"2026-04-14T13:48:21","slug":"mcp-server","status":"publish","type":"knowledgebase","link":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/","title":{"rendered":"MCP Server"},"content":{"rendered":"\n\n\n<h2 class=\"wp-block-heading\">Introduction<\/h2>\n\n\n\n<p>The <strong>Refiner MCP Server<\/strong> is an implementation of the <a href=\"https:\/\/github.com\/modelcontextprotocol?utm_source=chatgpt.com\">Model Context Protocol<\/a> that enables AI agents to securely interact with your Refiner account.<\/p>\n\n\n\n<p>It acts as a bridge between LLM-powered agents and customer feedback data, allowing automation of analytics, user management, and survey workflows through natural language.<\/p>\n\n\n\n<p>At a high level, this server exposes Refiner survey response data as structured tools that AI agents can discover and invoke dynamically.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">How to use our MCP server<\/h2>\n\n\n\n<p>With the Refiner MCP Server, you can connect your Refiner workspace directly to AI tools like ChatGPT and Claude to analyze survey responses on demand using natural language. This enables ad-hoc exploration of feedback data, from summarizing open-text responses to identifying trends and anomalies in real time. <\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"923\" src=\"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32-1024x923.png\" alt=\"\" class=\"wp-image-28438\" srcset=\"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32-1024x923.png 1024w, https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32-800x721.png 800w, https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32-768x692.png 768w, https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32.png 1442w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure><\/div>\n\n\n<p>Beyond analysis, you can power workflow automations &#8211; such as triggering actions based on new responses or syncing insights across systems &#8211; using tools like Claude Code. The result is a more dynamic, AI-driven feedback loop where insights can be generated and acted upon instantly without manual intervention.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">MCP server endpoint<\/h2>\n\n\n\n<p>The Refiner MCP server is reachable under the following URL:<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"raw\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">https:\/\/app.refiner.io\/v001\/mcp<\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">Authentication<\/h2>\n\n\n\n<p>Refiner MCP uses OAuth 2.0 Authorization Code + PKCE.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Discovery endpoints<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>https:\/\/app.refiner.io\/.well-known\/oauth-authorization-server<\/code><\/li>\n\n\n\n<li><code>https:\/\/app.refiner.io\/.well-known\/oauth-protected-resource<\/code><\/li>\n\n\n\n<li><code>https:\/\/app.refiner.io\/.well-known\/oauth-protected-resource\/v001\/mcp<\/code><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Scopes<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>mcp:projects-read<\/code> &#8211; list accessible environments\/projects<\/li>\n\n\n\n<li><code>mcp:forms-read<\/code> &#8211; read surveys\/forms<\/li>\n\n\n\n<li><code>mcp:responses-read<\/code> &#8211; read individual responses<\/li>\n\n\n\n<li><code>mcp:reporting-read<\/code> &#8211; read aggregated reporting data<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Tools<\/h2>\n\n\n\n<p>All tools are read-only and registered in <code>RefinerServer<\/code>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">get-aggregated-response-data<\/h3>\n\n\n\n<p>Get aggregated reporting and chart data. Requires project_uuid from get-projects. Filter by form UUIDs (surveys), segment UUIDs, tag UUIDs, question identifiers and date range. Chart types: nps, csat, ratings, count, distribution. The date range defaults to the past 30 days and can extend back up to 12 months.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Scope: <code>mcp:reporting-read<\/code><\/li>\n\n\n\n<li>Input: <code>project_uuid<\/code>, required <code>type<\/code>, optional <code>form_uuids<\/code>, <code>segment_uuids<\/code>, <code>tag_uuids<\/code>, <code>question_identifiers<\/code>, <code>date_range_start<\/code>, <code>date_range_end<\/code><\/li>\n\n\n\n<li><code>type<\/code>: <code>nps<\/code>, <code>csat<\/code>, <code>ratings<\/code>, <code>count<\/code>, <code>distribution<\/code><\/li>\n\n\n\n<li>Read-only<\/li>\n\n\n\n<li>Not destructive<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">get-forms<\/h3>\n\n\n\n<p>List surveys in a project. Requires project_uuid from get-projects. Available lists: all, all_with_archived, archived, published, drafts.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Scope: <code>mcp:forms-read<\/code><\/li>\n\n\n\n<li>Input: <code>project_uuid<\/code>, optional <code>page<\/code>, <code>list<\/code><\/li>\n\n\n\n<li><code>list<\/code>: <code>all<\/code>, <code>all_with_archived<\/code>, <code>archived<\/code>, <code>published<\/code>, <code>drafts<\/code><\/li>\n\n\n\n<li>Read-only<\/li>\n\n\n\n<li>Not destructive<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">get-projects<\/h3>\n\n\n\n<p>List surveys in a project. Requires project_uuid from get-projects. Available lists: all, all_with_archived, archived, published, drafts.<\/p>\n\n\n\n<p>Lists available projects.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Scope: <code>mcp:projects-read<\/code><\/li>\n\n\n\n<li>Input: none<\/li>\n\n\n\n<li>Output: <code>items[]<\/code> with <code>uuid<\/code>, <code>name<\/code><\/li>\n\n\n\n<li>Read-only<\/li>\n\n\n\n<li>Not destructive<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">get-responses<\/h3>\n\n\n\n<p>Get access to a list of survey responses. Requires project_uuid from get-projects. Filter by form UUIDs (surveys), segment UUIDs, tag UUIDs, and date range. Returns up to 500 responses per page. Contact data is excluded for privacy reasons. The date range defaults to the past 30 days and can extend back up to 12 months.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Scope: <code>mcp:responses-read<\/code><\/li>\n\n\n\n<li>Input: <code>project_uuid<\/code>, optional <code>form_uuids<\/code>, <code>segment_uuids<\/code>, <code>tag_uuids<\/code>, <code>date_range_start<\/code>, <code>date_range_end<\/code>, <code>page<\/code>, <code>page_cursor<\/code><\/li>\n\n\n\n<li>Notes:<\/li>\n\n\n\n<li>filters can be comma-separated UUID strings<\/li>\n\n\n\n<li>defaults to last 30 days<\/li>\n\n\n\n<li>max lookback 12 months<\/li>\n\n\n\n<li>up to 500 responses\/page<\/li>\n\n\n\n<li>contact data excluded for privacy<\/li>\n\n\n\n<li>Read-only<\/li>\n\n\n\n<li>Not destructive<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">get-segments<\/h3>\n\n\n\n<p>List user segments in a project. Requires project_uuid from get-projects.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Scope: <code>mcp:projects-read<\/code><\/li>\n\n\n\n<li>Input: <code>project_uuid<\/code><\/li>\n\n\n\n<li>Read-only<\/li>\n\n\n\n<li>Not destructive<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">get-traits<\/h3>\n\n\n\n<p>List response tags in a project. Requires project_uuid from get-projects.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Scope: <code>mcp:projects-read<\/code><\/li>\n\n\n\n<li>Input: <code>project_uuid<\/code>, optional <code>include<\/code><\/li>\n\n\n\n<li><code>include<\/code>: <code>all<\/code>, <code>form<\/code>, <code>contact<\/code><\/li>\n\n\n\n<li>Read-only<\/li>\n\n\n\n<li>Not destructive<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">get-tags<\/h3>\n\n\n\n<p>List attributes in a project. Requires project_uuid from get-projects. include options: all, form, contact.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Scope: <code>mcp:projects-read<\/code><\/li>\n\n\n\n<li>Input: <code>project_uuid<\/code><\/li>\n\n\n\n<li>Read-only<\/li>\n\n\n\n<li>Not destructive<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Resources<\/h2>\n\n\n\n<p>Resources provide URI-based reads for MCP clients that support resources.<\/p>\n\n\n\n<p>Available Resources:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>refiner:\/\/projects<\/code><\/li>\n\n\n\n<li><code>refiner:\/\/project\/{project_uuid}\/forms<\/code><\/li>\n\n\n\n<li><code>refiner:\/\/project\/{project_uuid}\/form\/{form_uuid}<\/code><\/li>\n\n\n\n<li><code>refiner:\/\/project\/{project_uuid}\/segments<\/code><\/li>\n\n\n\n<li><code>refiner:\/\/project\/{project_uuid}\/tags<\/code><\/li>\n<\/ul>\n\n\n\n<p>Behavior:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>MIME type: <code>application\/json<\/code><\/li>\n\n\n\n<li>Same scope and project-access checks as corresponding tools<\/li>\n\n\n\n<li>Consistent structured responses and explicit access errors<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Sample prompts<\/h2>\n\n\n\n<p>Refiner exposes built-in MCP prompts to guide robust multi-step analysis workflows.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Built-in prompts<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>nps_get_score_and_counts<\/code><\/li>\n\n\n\n<li><code>csat_get_score_and_counts<\/code><\/li>\n\n\n\n<li><code>multiple_choice_response_distribution<\/code><\/li>\n\n\n\n<li><code>retrieve_survey_responses<\/code><\/li>\n\n\n\n<li><code>nps_analyze_verbatim<\/code><\/li>\n\n\n\n<li><code>csat_analyze_verbatim<\/code><\/li>\n\n\n\n<li><code>analyze_open_ended_text_responses<\/code><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Example user prompts<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>&#8220;List my available Refiner environments and surveys.&#8221;<\/li>\n\n\n\n<li>&#8220;Show NPS score and detractor\/passive\/promoter counts for the last 30 days.&#8221;<\/li>\n\n\n\n<li>&#8220;Analyse recent NPS open-text verbatim and tell me which are the biggest drivers for the current score. Tell me what we do right and what we can improve based on the open-text verbatim.&#8221;<\/li>\n\n\n\n<li>&#8220;What is our current CSAT score in the X project in Refiner?&#8221;<\/li>\n\n\n\n<li>&#8220;Show CSAT score and distribution for survey X in Q1.&#8221;<\/li>\n\n\n\n<li>&#8220;Retrieve responses tagged <code>churn-risk<\/code> from the past 14 days.&#8221;<\/li>\n\n\n\n<li>&#8220;Analyze open-ended feedback and suggest top improvement actions.&#8221;<\/li>\n\n\n\n<li>&#8220;Show multiple-choice response distribution for question <code>onboarding_experience<\/code>.&#8221;<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Introduction The Refiner MCP Server is an implementation of the Model Context Protocol that enables AI agents to securely interact with your Refiner account. It acts as a bridge between LLM-powered agents and customer feedback data, allowing automation of analytics, user management, and survey workflows through natural language. At a high level, this server exposes [&#8230;]<\/p>\n<p><a class=\"btn btn-secondary understrap-read-more-link\" href=\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/\">Read More&#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","template":"","knowledgebase_tag":[],"class_list":["post-28420","knowledgebase","type-knowledgebase","status-publish","hentry","knowledgebase_cat-integrations"],"featured_image_urls_v2":{"full":"","thumbnail":"","medium":"","medium_large":"","large":"","1536x1536":"","2048x2048":"","ab-block-post-grid-landscape":"","ab-block-post-grid-square":"","gb-block-post-grid-landscape":"","gb-block-post-grid-square":""},"post_excerpt_stackable_v2":"<p>Introduction The Refiner MCP Server is an implementation of the Model Context Protocol that enables AI agents to securely interact with your Refiner account. It acts as a bridge between LLM-powered agents and customer feedback data, allowing automation of analytics, user management, and survey workflows through natural language. At a high level, this server exposes Refiner survey response data as structured tools that AI agents can discover and invoke dynamically. How to use our MCP server With the Refiner MCP Server, you can connect your Refiner workspace directly to AI tools like ChatGPT and Claude to analyze survey responses on&hellip;<\/p>\n","category_list_v2":"","author_info_v2":{"name":"Moritz Dausinger","url":"https:\/\/refiner.io\/docs\/author\/user\/"},"comments_num_v2":"0 comments","acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>MCP Server<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MCP Server\" \/>\n<meta property=\"og:description\" content=\"Introduction The Refiner MCP Server is an implementation of the Model Context Protocol that enables AI agents to securely interact with your Refiner account. It acts as a bridge between LLM-powered agents and customer feedback data, allowing automation of analytics, user management, and survey workflows through natural language. At a high level, this server exposes [...]Read More...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/\" \/>\n<meta property=\"og:site_name\" content=\"Refiner Documentation\" \/>\n<meta property=\"article:modified_time\" content=\"2026-04-14T13:48:21+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32-1024x923.png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/\",\"url\":\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/\",\"name\":\"MCP Server\",\"isPartOf\":{\"@id\":\"https:\/\/refiner.io\/docs\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32-1024x923.png\",\"datePublished\":\"2026-04-14T13:23:20+00:00\",\"dateModified\":\"2026-04-14T13:48:21+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#primaryimage\",\"url\":\"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32.png\",\"contentUrl\":\"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32.png\",\"width\":1442,\"height\":1300},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/refiner.io\/docs\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"MCP Server\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/refiner.io\/docs\/#website\",\"url\":\"https:\/\/refiner.io\/docs\/\",\"name\":\"Refiner Documentation\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/refiner.io\/docs\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/refiner.io\/docs\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/refiner.io\/docs\/#organization\",\"name\":\"Refiner Documentation\",\"url\":\"https:\/\/refiner.io\/docs\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/refiner.io\/docs\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2022\/11\/cropped-Group-8.png\",\"contentUrl\":\"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2022\/11\/cropped-Group-8.png\",\"width\":400,\"height\":61,\"caption\":\"Refiner Documentation\"},\"image\":{\"@id\":\"https:\/\/refiner.io\/docs\/#\/schema\/logo\/image\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"MCP Server","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/","og_locale":"en_US","og_type":"article","og_title":"MCP Server","og_description":"Introduction The Refiner MCP Server is an implementation of the Model Context Protocol that enables AI agents to securely interact with your Refiner account. It acts as a bridge between LLM-powered agents and customer feedback data, allowing automation of analytics, user management, and survey workflows through natural language. At a high level, this server exposes [...]Read More...","og_url":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/","og_site_name":"Refiner Documentation","article_modified_time":"2026-04-14T13:48:21+00:00","og_image":[{"url":"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32-1024x923.png"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"3 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/","url":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/","name":"MCP Server","isPartOf":{"@id":"https:\/\/refiner.io\/docs\/#website"},"primaryImageOfPage":{"@id":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#primaryimage"},"image":{"@id":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#primaryimage"},"thumbnailUrl":"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32-1024x923.png","datePublished":"2026-04-14T13:23:20+00:00","dateModified":"2026-04-14T13:48:21+00:00","breadcrumb":{"@id":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#primaryimage","url":"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32.png","contentUrl":"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2026\/04\/Screenshot-2026-04-14-at-15.45.32.png","width":1442,"height":1300},{"@type":"BreadcrumbList","@id":"https:\/\/refiner.io\/docs\/kb\/integrations\/mcp-server\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/refiner.io\/docs\/"},{"@type":"ListItem","position":2,"name":"MCP Server"}]},{"@type":"WebSite","@id":"https:\/\/refiner.io\/docs\/#website","url":"https:\/\/refiner.io\/docs\/","name":"Refiner Documentation","description":"","publisher":{"@id":"https:\/\/refiner.io\/docs\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/refiner.io\/docs\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/refiner.io\/docs\/#organization","name":"Refiner Documentation","url":"https:\/\/refiner.io\/docs\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/refiner.io\/docs\/#\/schema\/logo\/image\/","url":"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2022\/11\/cropped-Group-8.png","contentUrl":"https:\/\/refiner.io\/docs\/wp-content\/uploads\/2022\/11\/cropped-Group-8.png","width":400,"height":61,"caption":"Refiner Documentation"},"image":{"@id":"https:\/\/refiner.io\/docs\/#\/schema\/logo\/image\/"}}]}},"_links":{"self":[{"href":"https:\/\/refiner.io\/docs\/wp-json\/wp\/v2\/knowledgebase\/28420","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/refiner.io\/docs\/wp-json\/wp\/v2\/knowledgebase"}],"about":[{"href":"https:\/\/refiner.io\/docs\/wp-json\/wp\/v2\/types\/knowledgebase"}],"author":[{"embeddable":true,"href":"https:\/\/refiner.io\/docs\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/refiner.io\/docs\/wp-json\/wp\/v2\/comments?post=28420"}],"version-history":[{"count":12,"href":"https:\/\/refiner.io\/docs\/wp-json\/wp\/v2\/knowledgebase\/28420\/revisions"}],"predecessor-version":[{"id":28442,"href":"https:\/\/refiner.io\/docs\/wp-json\/wp\/v2\/knowledgebase\/28420\/revisions\/28442"}],"wp:attachment":[{"href":"https:\/\/refiner.io\/docs\/wp-json\/wp\/v2\/media?parent=28420"}],"wp:term":[{"taxonomy":"knowledgebase_tag","embeddable":true,"href":"https:\/\/refiner.io\/docs\/wp-json\/wp\/v2\/knowledgebase_tag?post=28420"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}