41 boosters for "llms" — open source, verified from GitHub, ready to install
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Heuristic scoring (no AI key configured).
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.
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.
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.
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.
MetehanGZL Pokemcp provides developers with detailed Pokémon data and information through a standardized MCP interface, enabling AI assistants to access comprehensive game information for building Pokémon-related applications and features.
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.
