Today's AI Frameworks & SDKs: Fastest-Growing Projects — April 20, 2026
Today's AI Frameworks & SDKs, we're seeing a surge in tools that enable more efficient and accessible development of artificial intelligence applications. Many of these projects are focused on creating infrastructure for language models, multimodal modeling, and decentralized AI computing. This trend suggests a growing demand for more robust and flexible frameworks to support the rapid advancement of AI research and development.
jxnxts/mcp-brasil is gaining traction with a Growth Score of 51.50 and 1,408 stars, as it provides an MCP server for 41 public Brazilian APIs, allowing developers to easily integrate these services into their applications. Its high growth rate can be attributed to the increasing demand for accessible and standardized API infrastructure in Brazil.
Agent-FM/agentfm-core has a Growth Score of 33.33 and 63 stars, as it offers a peer-to-peer network that enables decentralized AI supercomputing by harnessing idle CPU and GPU resources from everyday computers. Its growth is driven by the need for more efficient and cost-effective ways to run massive AI workloads.
yogthos/chiasmus boasts a Growth Score of 25.88 and 61 stars, providing an MCP server that gives language models access to formal verification. Its increasing popularity can be attributed to the growing importance of robustness and reliability in language model development.
Tencent-Hunyuan/HY-SOAR has a Growth Score of 22.00 and 95 stars, introducing a self-correction method for optimal alignment and refinement in diffusion models. Despite having fewer commits, its growth is notable due to the rising interest in improving the accuracy and efficiency of diffusion models.
416rehman/DeepZero sports a Growth Score of 21.08 and 95 stars, offering an automated vulnerability research framework that uses AI agents to analyze Windows kernel drivers for exploitable IOCTLs. Its growth can be attributed to the increasing demand for more efficient and effective vulnerability detection methods in cybersecurity.
OpenEnvision/Awesome-Multimodal-Modeling has a Growth Score of 18.85 and 257 stars, providing a comprehensive resource list for multimodal modeling. Its popularity is driven by the growing interest in multimodal applications and the need for a centralized knowledge base.
codefromkarl/ContextAtlas boasts a Growth Score of 18.47 and 25 stars, offering context infrastructure for AI coding agents through hybrid retrieval, project memory, and retrieval observability. Its growth can be attributed to the increasing demand for more efficient and organized ways to manage context in AI development.
rhino-acoustic/NeuronFS has a Growth Score of 16.18 and 137 stars, introducing a B-tree-based file system optimized for AI applications with zero-byte folders and improved token efficiency. Its growth is driven by the need for more efficient and specialized infrastructure for large-scale AI projects.
FANzR-arch/Numerologist_skills has a Growth Score of 15.58 and 495 stars, providing an engineering framework to reduce hallucinations in Chinese astrology language models. Despite having fewer commits, its high star count suggests significant interest in this niche application.
JiaboLi-GitHub/renderdoc-mcp has a Growth Score of 14.98 and 125 stars, offering an MCP server for RenderDoc that enables AI assistants to analyze GPU frame captures and debug graphics pipelines. Its growth can be attributed to the increasing demand for more efficient and accessible debugging tools in computer graphics development.
jxnxts/mcp-brasil is gaining traction with a Growth Score of 51.50 and 1,408 stars, as it provides an MCP server for 41 public Brazilian APIs, allowing developers to easily integrate these services into their applications. Its high growth rate can be attributed to the increasing demand for accessible and standardized API infrastructure in Brazil.
Agent-FM/agentfm-core has a Growth Score of 33.33 and 63 stars, as it offers a peer-to-peer network that enables decentralized AI supercomputing by harnessing idle CPU and GPU resources from everyday computers. Its growth is driven by the need for more efficient and cost-effective ways to run massive AI workloads.
yogthos/chiasmus boasts a Growth Score of 25.88 and 61 stars, providing an MCP server that gives language models access to formal verification. Its increasing popularity can be attributed to the growing importance of robustness and reliability in language model development.
Tencent-Hunyuan/HY-SOAR has a Growth Score of 22.00 and 95 stars, introducing a self-correction method for optimal alignment and refinement in diffusion models. Despite having fewer commits, its growth is notable due to the rising interest in improving the accuracy and efficiency of diffusion models.
416rehman/DeepZero sports a Growth Score of 21.08 and 95 stars, offering an automated vulnerability research framework that uses AI agents to analyze Windows kernel drivers for exploitable IOCTLs. Its growth can be attributed to the increasing demand for more efficient and effective vulnerability detection methods in cybersecurity.
OpenEnvision/Awesome-Multimodal-Modeling has a Growth Score of 18.85 and 257 stars, providing a comprehensive resource list for multimodal modeling. Its popularity is driven by the growing interest in multimodal applications and the need for a centralized knowledge base.
codefromkarl/ContextAtlas boasts a Growth Score of 18.47 and 25 stars, offering context infrastructure for AI coding agents through hybrid retrieval, project memory, and retrieval observability. Its growth can be attributed to the increasing demand for more efficient and organized ways to manage context in AI development.
rhino-acoustic/NeuronFS has a Growth Score of 16.18 and 137 stars, introducing a B-tree-based file system optimized for AI applications with zero-byte folders and improved token efficiency. Its growth is driven by the need for more efficient and specialized infrastructure for large-scale AI projects.
FANzR-arch/Numerologist_skills has a Growth Score of 15.58 and 495 stars, providing an engineering framework to reduce hallucinations in Chinese astrology language models. Despite having fewer commits, its high star count suggests significant interest in this niche application.
JiaboLi-GitHub/renderdoc-mcp has a Growth Score of 14.98 and 125 stars, offering an MCP server for RenderDoc that enables AI assistants to analyze GPU frame captures and debug graphics pipelines. Its growth can be attributed to the increasing demand for more efficient and accessible debugging tools in computer graphics development.