agent-library: Agent Library provides AI agents with persistent storage for text, documents, and knowledge using SQLite with vector search (sqlite-vec) and full-text search (FTS5). It supports hybrid search combining semantic and keyword matching, configurable embedding models, and offers both CLI and MCP server interfaces for integration.; context-mode: Every tool call in an MCP (Model-Controller-Program) environment dumps raw data into the context window, quickly consuming space and causing the agent to lose track of ongoing tasks. Context Mode is an MCP server that tackles this by sandboxing tool outputs to significantly reduce context usage, tracking session events in SQLite for continuity, and promoting 'think in code' to minimize data processing within the LLM.
Storing and retrieving agent memories across conversations
Deep repository research and analysis (e.g., architecture, contributors, issues)