{"id":2959,"date":"2026-03-28T12:47:17","date_gmt":"2026-03-28T12:47:17","guid":{"rendered":"https:\/\/www.mhtechin.com\/support\/?p=2959"},"modified":"2026-03-28T12:47:17","modified_gmt":"2026-03-28T12:47:17","slug":"mhtechin-open-source-agent-leaderboards-which-framework-wins","status":"publish","type":"post","link":"https:\/\/www.mhtechin.com\/support\/mhtechin-open-source-agent-leaderboards-which-framework-wins\/","title":{"rendered":"MHTECHIN \u2013 Open-Source Agent Leaderboards: Which Framework Wins?"},"content":{"rendered":"\n<h3 class=\"wp-block-heading\">Introduction<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The rapid evolution of AI agents has led to the rise of multiple frameworks designed to simplify development, orchestration, and deployment. With so many options available, developers and organizations often ask a critical question: <strong>Which AI agent framework performs best?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To answer this, the industry relies on <strong>open-source agent leaderboards<\/strong>\u2014benchmarking systems that evaluate frameworks based on performance, reasoning ability, tool usage, and real-world task completion.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Organizations such as OpenAI, Google, and Microsoft contribute to or influence these ecosystems, making leaderboards an essential reference for AI development decisions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This guide by MHTECHIN provides a deep, theory-focused analysis of open-source agent leaderboards, comparing top frameworks and helping you determine which one \u201cwins\u201d based on your use case.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">What Are Open-Source Agent Leaderboards?<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">Definition<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Open-source agent leaderboards are benchmarking platforms that evaluate AI agent frameworks using standardized tasks and metrics.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">They measure how well agents can:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Understand instructions<\/li>\n\n\n\n<li>Plan multi-step tasks<\/li>\n\n\n\n<li>Use tools effectively<\/li>\n\n\n\n<li>Maintain context<\/li>\n\n\n\n<li>Produce accurate outputs<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Purpose of Leaderboards<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Leaderboards help:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Compare frameworks objectively<\/li>\n\n\n\n<li>Identify strengths and weaknesses<\/li>\n\n\n\n<li>Guide framework selection<\/li>\n\n\n\n<li>Drive innovation in AI systems<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">How AI Agent Frameworks Are Evaluated<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">Key Evaluation Metrics<\/h4>\n\n\n\n<h5 class=\"wp-block-heading\">Task Success Rate<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">Measures how often an agent successfully completes a task.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h5 class=\"wp-block-heading\">Reasoning Capability<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">Evaluates the agent\u2019s ability to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Break down problems<\/li>\n\n\n\n<li>Follow logical steps<\/li>\n\n\n\n<li>Handle complex scenarios<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h5 class=\"wp-block-heading\">Tool Usage Efficiency<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">Assesses how effectively agents:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Call APIs<\/li>\n\n\n\n<li>Use external tools<\/li>\n\n\n\n<li>Retrieve data<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h5 class=\"wp-block-heading\">Latency and Speed<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">Measures response time and execution efficiency.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h5 class=\"wp-block-heading\">Cost Efficiency<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">Evaluates token usage and computational cost.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h5 class=\"wp-block-heading\">Robustness<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">Tests how well agents handle:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Edge cases<\/li>\n\n\n\n<li>Ambiguous inputs<\/li>\n\n\n\n<li>Failures<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">Visualization of Agent Benchmarking<\/h3>\n\n\n\n<figure class=\"wp-block-image aligncenter is-resized\"><img decoding=\"async\" src=\"https:\/\/images.openai.com\/static-rsc-4\/pqexqRHr-W78_ghZLryUXoBOsErekFHMFSowXSVzB3tGEmQcz5Ugaj6HgnOazlqa7wpoEAnvqdEdlQHXiT04_M_jVe9AFacI4BXQh3jiMT4v4CeOfrzBmm4N_MlN8hIOEny2rbP8NuFQtzjmXStxh91T_NNb9rvbmCHRppxgiXQ?purpose=inline\" alt=\"https:\/\/images.openai.com\/static-rsc-4\/u-ecHVSG1_WVJYxpbmsNyRLgrJeNfaZX9Gb5fwKSVNm0OlARHYoXsOaLJoTGPZLMWDWbefu5jRSZ2syh4o7gx54-bzA_8CSOzmnztw-29ksTEMBTdHGYcAJL7Gisw_r-VYFZNpVCKX01ZJ8ocGqxeEf2-xo_TY0oawhN-6IcnnbxjtlK-fX1joZQGeQrL1xt?purpose=fullsize\" style=\"aspect-ratio:1.7860697813794721;width:795px;height:auto\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image aligncenter is-resized\"><img decoding=\"async\" src=\"https:\/\/images.openai.com\/static-rsc-4\/B-7GeBc-1dvkck6O3FS8lrZFk8_MwSuHmQ_xK5NC6ICN24P1I_iPyoHBsVdWF7N2WBQulrhHnBWqbfV4RIYs0cBnsJxEs8g3M3PiobytJ49lgZrMB7GM3bgWuhgnJbwgUUfYkElgpbETDfmgnvkII-1hYXRuTA-wVQD1UCuHuT8?purpose=inline\" alt=\"https:\/\/images.openai.com\/static-rsc-4\/1ZQ4ImUno5AQOUr6gqv8bw704Fok-ndUsInUnvEFRCHCA8lrsTMr44YSYBJy7pKg5MNq68E6F4Sky0G4wU2yzcI6i2lretaRhCbJTTTfnSKNcPIAoGwtoqmR63JxljX8KOICYPMHep9kQsxYT_1gBUz4cxP1_1AApHgcisV-HMlrmtAfTCqGW1kjtZX6zNvJ?purpose=fullsize\" style=\"width:711px;height:auto\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image aligncenter is-resized\"><img decoding=\"async\" src=\"https:\/\/images.openai.com\/static-rsc-4\/WO6wpJInAMrKPJfeKdv_R-mojzBSxISKL1L2i-x4iZAiYG7sjxr7LvHWHRsjU0OXlzkrWImGnFD0-aIf4N8IYHgXu66G1A4cDspDP7fyO0Cf0M-w-sXyRUSLyCwdDTYmg2YX-TD_37fmyyhE8hyJrSOnjJzqbat7cdW_NbhfjjU?purpose=inline\" alt=\"https:\/\/images.openai.com\/static-rsc-4\/jX1Ix8iiHi3ASvblu1UVcqjknLXqLZBTYiLY0YnZ1wTGVAUZG7U4p1fpesR7zJ4OgsipZv1I9zGv09eLxco1ZhZeNwFABnj7IFmHd3yOUtLw-lrKMUG_iNIUTST4qarvvCGLf_gLBCY_jLvNd7e26Vidlruot-rKpkaUt3AUXfYlS45fg_E14IJ4dlumu1t4?purpose=fullsize\" style=\"aspect-ratio:1.9551600205373951;width:716px;height:auto\" \/><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">Popular Open-Source Agent Frameworks<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">1. LangChain<\/h4>\n\n\n\n<h5 class=\"wp-block-heading\">Overview<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">LangChain is one of the most widely used frameworks for building AI agents.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Strengths<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Strong ecosystem<\/li>\n\n\n\n<li>Flexible integrations<\/li>\n\n\n\n<li>Good for rapid development<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">Weaknesses<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Can become complex at scale<\/li>\n\n\n\n<li>Debugging can be challenging<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">2. AutoGPT<\/h4>\n\n\n\n<h5 class=\"wp-block-heading\">Overview<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">AutoGPT focuses on autonomous agents capable of self-directed tasks.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Strengths<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>High autonomy<\/li>\n\n\n\n<li>Experimental innovation<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">Weaknesses<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Less predictable outputs<\/li>\n\n\n\n<li>Higher cost and latency<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">3. BabyAGI<\/h4>\n\n\n\n<h5 class=\"wp-block-heading\">Overview<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">BabyAGI is a lightweight framework for task management and execution.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Strengths<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Simple architecture<\/li>\n\n\n\n<li>Easy to understand<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">Weaknesses<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Limited scalability<\/li>\n\n\n\n<li>Basic capabilities<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">4. CrewAI<\/h4>\n\n\n\n<h5 class=\"wp-block-heading\">Overview<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">CrewAI specializes in multi-agent collaboration.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Strengths<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Strong multi-agent workflows<\/li>\n\n\n\n<li>Role-based agent design<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">Weaknesses<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Still evolving<\/li>\n\n\n\n<li>Limited benchmarking data<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">5. MetaGPT<\/h4>\n\n\n\n<h5 class=\"wp-block-heading\">Overview<\/h5>\n\n\n\n<p class=\"wp-block-paragraph\">MetaGPT simulates software teams using multiple agents.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Strengths<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Structured workflows<\/li>\n\n\n\n<li>Strong reasoning capabilities<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\">Weaknesses<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Complex setup<\/li>\n\n\n\n<li>Resource-intensive<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">Leaderboard Insights: Which Framework Wins?<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">There Is No Single Winner<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Different frameworks excel in different areas. Leaderboards show that performance depends heavily on <strong>use case<\/strong>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Best for Beginners<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>LangChain<\/li>\n\n\n\n<li>Easy to start<\/li>\n\n\n\n<li>Large community support<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Best for Autonomous Agents<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>AutoGPT<\/li>\n\n\n\n<li>High independence<\/li>\n\n\n\n<li>Suitable for experimental projects<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Best for Multi-Agent Systems<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>CrewAI<\/li>\n\n\n\n<li>Role-based collaboration<\/li>\n\n\n\n<li>Scalable workflows<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Best for Research and Innovation<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>MetaGPT<\/li>\n\n\n\n<li>Advanced reasoning<\/li>\n\n\n\n<li>Complex task execution<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Best for Simplicity<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>BabyAGI<\/li>\n\n\n\n<li>Lightweight<\/li>\n\n\n\n<li>Easy to implement<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">Factors to Consider When Choosing a Framework<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">Project Complexity<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Simple tasks \u2192 Lightweight frameworks<\/li>\n\n\n\n<li>Complex systems \u2192 Advanced frameworks<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Scalability Requirements<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Large-scale applications require robust orchestration<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Performance Needs<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Low latency vs high reasoning capability<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Cost Constraints<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Token usage varies across frameworks<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Ecosystem and Community<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Active communities provide better support and updates<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">Limitations of Agent Leaderboards<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">Benchmark Bias<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Leaderboards may favor certain tasks or models, not reflecting real-world performance.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Rapidly Changing Ecosystem<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">AI frameworks evolve quickly, making rankings temporary.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Lack of Standardization<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Different benchmarks use different evaluation methods.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">MHTECHIN Perspective on Framework Selection<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">MHTECHIN emphasizes that choosing a framework should be based on <strong>practical requirements<\/strong>, not just leaderboard rankings.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Recommended Approach<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Start with a flexible framework<\/li>\n\n\n\n<li>Test performance on real use cases<\/li>\n\n\n\n<li>Optimize based on feedback<\/li>\n\n\n\n<li>Scale using advanced orchestration<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">This ensures long-term success rather than short-term gains.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">Future of AI Agent Leaderboards<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The future will likely include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Standardized evaluation metrics<\/li>\n\n\n\n<li>Real-world benchmarking scenarios<\/li>\n\n\n\n<li>Integration with MLOps pipelines<\/li>\n\n\n\n<li>Continuous performance tracking<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Leaderboards will evolve from static rankings to <strong>dynamic performance monitoring systems<\/strong>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">Conclusion<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Open-source agent leaderboards provide valuable insights into the performance of AI frameworks, but there is no universal winner. Each framework has strengths and trade-offs, making it essential to choose based on specific needs.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Rather than relying solely on rankings, developers should focus on:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Use-case alignment<\/li>\n\n\n\n<li>Performance testing<\/li>\n\n\n\n<li>Scalability considerations<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">MHTECHIN highlights that the best framework is not the one that ranks highest, but the one that <strong>fits your system architecture and business goals<\/strong>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h3 class=\"wp-block-heading\">FAQ (Optimized for Featured Snippets)<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">What are AI agent leaderboards?<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">They are benchmarking systems that evaluate AI agent frameworks based on performance and capabilities.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Which AI agent framework is best?<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">There is no single best framework; it depends on the use case and requirements.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">What metrics are used in agent leaderboards?<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Common metrics include task success rate, reasoning ability, latency, and cost efficiency.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">Is LangChain the best framework?<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">LangChain is popular and versatile but may not be the best choice for every use case.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h4 class=\"wp-block-heading\">How should I choose an AI agent framework?<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Consider factors like complexity, scalability, cost, and ecosystem support.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Introduction The rapid evolution of AI agents has led to the rise of multiple frameworks designed to simplify development, orchestration, and deployment. With so many options available, developers and organizations often ask a critical question: Which AI agent framework performs best? To answer this, the industry relies on open-source agent leaderboards\u2014benchmarking systems that evaluate frameworks [&hellip;]<\/p>\n","protected":false},"author":67,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2959","post","type-post","status-publish","format-standard","hentry","category-support"],"_links":{"self":[{"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/posts\/2959","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/users\/67"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/comments?post=2959"}],"version-history":[{"count":1,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/posts\/2959\/revisions"}],"predecessor-version":[{"id":2960,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/posts\/2959\/revisions\/2960"}],"wp:attachment":[{"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/media?parent=2959"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/categories?post=2959"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/tags?post=2959"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}