AgentDB Vector Search
High-performance vector search engine for AI agents featuring sub-millisecond retrieval, HNSW indexing, and quantization for efficient RAG, similarity matching, and knowledge base management.
Curated agent skills for semantic search — compare tools, clone hosted repos, and install with Skill Manager.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
24 skills found
High-performance vector search engine for AI agents featuring sub-millisecond retrieval, HNSW indexing, and quantization for efficient RAG, similarity matching, and knowledge base management.
Implement high-performance persistent memory and self-learning patterns for AI agents using AgentDB. Features session memory, long-term vector storage, and hierarchical context management for stateful agent workflows.
Advanced browser automation for research, web interaction, and data extraction within secure container environments.
An AI-powered TestOps platform and MCP server providing automated failure analysis, RCA matching, and intelligent test orchestration for CI/CD pipelines.
An AI-powered skill that automatically retrieves relevant project context from your RAG knowledge base for complex coding tasks.
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
A nested plugin architecture for Claude Code that optimizes context by dynamically loading playbooks, skills, and agents to save over 90% in token usage.
Essential guide to llmemory for document storage and search: installation, database setup with pgvector, document ingestion, hybrid/semantic retrieval, and building RAG systems with multi-tenant support.
Token-efficient codebase analysis skill for call graphs, semantic search, impact analysis, and data flow. Saves ~95% tokens vs. raw reads.
Persistent, Git-friendly memory for Claude. Automatically store and retrieve project decisions, bug fixes, and coding patterns in a local .mv2 file.
Build RAG systems to ground LLMs in proprietary data. Includes vector database integration, embedding strategies, hybrid search, and advanced retrieval patterns for FastAPI backends.
Interactive Archon integration for knowledge base and project management. Features RAG-powered semantic search, website crawling, document versioning, and hierarchical task management via REST API.