vector-search MCP servers & tools

Persistent fractal graph memory for AI coding agents via MCP. Semantic vector search, hot/cold/archive context tiers, decision tracking, and Docker-based deployment with Qdrant.

Dual-memory MCP system (PostgreSQL 17 + pgvector + NVIDIA NIM). 11 tools: search, save, profile, health, auto-repair, stats, tune, dedup, checkpoint, maintenance. Sparse Selective Caching (SSC) with 4-phase progressive retrieval. Bilingual EN/ES. python scripts/hipocampomcpserver.py

An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context

Local-first memory system for AI agents with hybrid search and graph reasoning

Shared memory + orchestration for your coding agents. Local-first MCP, vector RAG.

Local Markdown search, navigation and editing via MCP, with optional vector embeddings.