393 boosters for "LLM" — open source, verified from GitHub, ready to install
Markitai is an opinionated Markdown converter with native LLM enhancement support, designed to help developers using GitHub Copilot maintain consistent code standards and project guidelines. It's ideal for teams managing Python projects with strict type annotations, code style, and testing requirements.
A practical integration guide for enhancing OCR text extraction with visual and language LLM capabilities using local Ollama models in Caption Extractor. Developers working with document processing, image analysis, and text correction workflows benefit from this reusable agent framework.
A hierarchical multi-agent system that organizes 19 specialized AI agents into teams with intelligent LLM-based routing and dynamic tool binding for AI-assisted development tasks. Developers building complex AI-powered applications benefit from its modular architecture and industry-standard prompt integration.
An LLM-optimized TickTick task management MCP server that reduces token costs by 70% through intelligent time handling, enabling efficient AI-assisted task automation for productivity-focused developers and AI assistants.
Vibex Task Manager is an MCP server that integrates task management into AI-driven development workflows using AWS Bedrock, enabling developers to manage projects directly within Cursor and Claude environments.
Heuristic scoring (no AI key configured).
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.
PRISM is a prompt IDE that helps engineers design, test, and iterate on LLM prompts and agents through visual templates and dataset-driven feedback. It benefits prompt engineers, product teams, and developers building AI-powered applications who need structured prompt management and testing workflows.
A system prompt that enables LLMs to classify Hacker News content into mutually exclusive LLM and software development categories using context-aware analysis. Useful for content curators, researchers, and developers building topic-classification systems.
