supermemory
Supermemory is a long-term memory infrastructure for AI agents, enabling persistent context, user profiles, and semantic RAG across multi-modal knowledge bases.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
497 skills found
Supermemory is a long-term memory infrastructure for AI agents, enabling persistent context, user profiles, and semantic RAG across multi-modal knowledge bases.
A command-line interface for managing food delivery orders, currently supporting Foodora with Deliveroo integration in development.
Easily configure and add Model Context Protocol (MCP) servers to various AI coding clients like Cursor, Claude, VS Code, and more using an interactive or automated command-line interface.
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Accelerate software delivery by shifting testing to the earliest development phases, using AI-driven requirements validation, TDD, and automated CI pipelines to reduce defect costs.
Intelligently migrate existing brownfield projects to the AgenticDev structure using AI-powered analysis to reorganize documentation, generate rich frontmatter, and preserve git history.
A suite of professional tools for auditing, evaluating, chunking, and scaffolding production-ready RAG pipelines within Claude Code.
Standardize repo commands with justfiles. Define, organize, and document cross-platform workflows, aliases, and automation tasks to create a single source of truth for repository operations.
Comprehensive SEO and GEO optimization suite. Use to analyze domains, find keyword gaps, research backlinks, and generate autocomplete search suggestions using DataForSEO.
Generate daily and weekly planning reports from backlog and carryover state, applying WIP limits and priority rules from BaseContext.yaml with automatic git commit/push.
Teacher-focused student profiling tool: OCR answer sheets, summarize performance, and update student profiles with targeted physics learning goals.
The final execution agent for the vibe-coding workflow. Builds your MVP incrementally by following the AGENTS.md master plan, managing session continuity, and verifying each feature via testing.