49 boosters for "lms" — open source, verified from GitHub, ready to install
NextAuth v5 expert agent that provides JWT, OAuth, and multi-tenant authentication guidance for Next.js applications with role-based access control. Ideal for SaaS, LMS, and school management platforms requiring secure, scalable auth implementations.
This MCP server dynamically exposes Swagger/OpenAPI endpoints as callable tools for Claude and other LLMs, enabling AI agents to seamlessly integrate with REST APIs without manual tool definition. Developers building LLM applications that need to interact with documented APIs benefit most from this adapter.
THOR Skills is a router skill for LLMs that guides users through THOR security scanner operations—from running scans and analyzing logs to troubleshooting and writing plugins. It's valuable for security professionals, forensic analysts, and DevOps teams working with THOR malware scanning on endpoints.
Dreamfactory MCP Server enables Claude to access governed APIs across any enterprise data source through DreamFactory's self-hosted platform, benefiting enterprise developers and LLM integrators needing secure, standardized data access.
A TypeScript MCP server booster for integrating the ReviewWebsite API with Windsurf, providing CLI tools, validation schemas, and structured patterns for AI-assisted development. Ideal for developers building AI-powered review applications or extending Windsurf with ReviewWebsite capabilities.
Dossier is an MCP server that enables LLMs to discover, verify, and execute dossiers—standardized automation workflows. It's useful for developers and AI teams who want to automate complex, multi-step tasks through Claude and other AI platforms.
ArmBench-LLM is a system prompt for benchmarking large language models using Armenian character-to-numeric matching tasks. It's designed for developers evaluating LLM performance across multiple coding platforms.
ArmBench-LLM is a system prompt framework for evaluating large language models on Armenian language tasks through structured multiple-choice questions. It's designed for developers and AI researchers who need standardized benchmarking tools across popular coding assistants and chat platforms.
This MCP Server converts Figma designs into pseudo-code structures that LLMs can easily understand, enabling seamless design-to-code workflows for developers and designers building prototypes and applications.
"name": "frane-agented", "name": "Frane Bandov", "email": "frane.bandov@gmail.com"
Node Code Sandbox MCP enables AI agents and LLMs to safely execute JavaScript code, install npm packages, and test implementations in real-time. Developers building coding assistants, automated testing tools, and interactive AI applications benefit from this secure, MCP-compliant execution environment.
A system prompt that guides LLMs to act as rigorous sustainability and risk analysts for Polkadot governance proposals, evaluating treasury allocations through investment frameworks, fiscal precedent, and accountability mechanisms.
Intent Kit provides Cursor rules for building hierarchical intent-driven Python workflows with LLMs, enabling developers to create structured, context-aware automation systems. It's useful for developers building complex AI-driven applications that require intent classification and conditional execution.
gllm is a system prompt that transforms LLMs into code-first orchestrators for efficient task processing, enabling developers to handle large files and complex workflows through programmatic verification rather than context-heavy text generation.
An MCP server that integrates llmstxt documentation fetching into Claude Desktop and Claude Code, enabling developers to access and reference documentation within their AI-assisted workflows.
This system prompt enables smaller LLMs (8B-20B parameters) to control Windows 11 desktops through the Model Context Protocol, automating desktop tasks via natural language. It's valuable for developers building AI agents, automation workflows, and users seeking lightweight local alternatives to cloud-based desktop controllers.
Cursor rules for Learnology AI LMS that guide developers to wrap UI components with LunaContextElement and provide structured context data for AI assistant integration. Useful for teams building AI-enhanced learning management systems.
An expert prompt engineering agent that optimizes prompts for LLMs and AI systems, helping developers build better AI features and improve agent performance through proven prompt patterns and techniques.
"id": "ac.inference.sh/mcp", "name": "inference.sh", "description": "Run 150+ AI apps — image, video, audio, LLMs, 3D and more. Browse, execute, stream results."
A specialized agent that systematically crafts, tests, and optimizes prompts for LLMs through multiple cognitive modes (generative, critical, evaluative, informative) and performance measurement. Ideal for AI engineers, prompt researchers, and developers seeking to maximize LLM output quality.
Clara is a privacy-focused, client-side WebUI for interacting with LLMs without any backend infrastructure or data leaks. Developers and privacy-conscious users who want complete control over their AI conversations benefit from this tool.
A specialized agent that systematically crafts and optimizes prompts for LLMs and AI systems through iterative refinement and performance measurement. Ideal for AI engineers, prompt designers, and developers who need to maximize LLM effectiveness across applications.
An MCP server that enables LLMs to inspect, test, and debug other MCP servers, helping developers validate and troubleshoot their MCP implementations. Ideal for MCP developers, AI agents, and anyone building or integrating multiple MCP servers.
Heuristic scoring (no AI key configured).
