A local knowledge graph MCP server that provides AI agents with permanent, structured memory about codebases, enabling semantic search, blast radius analysis, and convention enforcement.
An in-memory knowledge graph MCP server that gives coding agents structural and semantic recall over codebases by indexing Python source, ADR documents, and project configuration, exposing 7 tools for search, traversal, context retrieval, and natural-language Q&A.
A local-first compiled knowledge graph MCP server that provides structured memory for AI agents with full-text search, vector embeddings, and timeline tracking.
A universal MCP server providing persistent, structured memory through a knowledge graph with graph storage, semantic vector search, and multi-hop traversal for AI agents and IDEs.
A persistent, event-sourced knowledge graph MCP server for AI coding agents that enables semantic search, tiered context retrieval, and git-based version control of AI memory.
Model-agnostic code memory MCP server using budget-aware graph retrieval for AI agents, providing sub-millisecond queries, token budgeting, and deterministic results without embeddings or vector databases.