A local-first MCP server that gives AI coding agents durable project memory, dependency graphs, and impact analysis to answer team knowledge and cross-file change questions before editing.
MCP server that gives AI coding assistants persistent memory, structural code graph analysis, and safe multi-agent coordination, enabling them to answer architectural questions, track decisions across sessions, and coordinate safely in multi-agent workflows.
MCP server for semantic code search and explanation. Allows AI agents to search, ask questions, and manage memory about a codebase with local embeddings and LLM integration.
Persistent memory MCP server that remembers decisions and context across coding sessions, automatically logging and surfacing relevant knowledge as you work.
MCP server that provides a shared semantic memory layer for AI coding agents, enabling teams to store, search, and sync context, decisions, and knowledge across projects with project-based isolation and multi-backend support.