Zaxy
Related Servers
Alternatives to Zaxy
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityAmaintenanceAudit-grade memory backbone for agent teams. Bi-temporal facts (event time + transaction time, with recall(as_of=...) replay), 6-step deterministic retrieval (no LLM in the critical path), conversation ingest with speaker-locked dual-pass extraction, per-tenant Postgres row-level security, and Ed25519-signed provenance. Postgres + pgvector + Neo4j defaults.42 PyPI14MIT
- AlicenseNot gradedqualityAmaintenanceLocal-first, source-grounded memory for AI agents, with citations, bitemporal history, review-gated corrections, and MCP tools for search and recall.46 PyPI3Apache 2.0

Mandrelofficial
AlicenseNot gradedqualityBmaintenanceEnables AI coding agents to maintain structured, persistent memory as a typed-edge knowledge graph over contexts, decisions, and tasks, with deterministic auto-threading, trust signals, and replayable story recall. It also exposes a token-lean MCP gateway for on-demand tool discovery, helping agents preserve causal project context across sessions.5,080 npm5MIT- AlicenseNot gradedqualityAmaintenanceProvides local-first persistent memory with a typed knowledge graph and bounded multi-hop retrieval via MCP, letting coding agents and local LLM systems store, search, and recall facts across sessions without hosted services or model dependencies.MIT

Lians Agent Memoryofficial
AlicenseAqualityCmaintenanceLocal-first bitemporal memory for AI agents with deterministic supersession, point-in-time recall, erasure proofs, and tamper-evident audit history.916Apache 2.0- AlicenseNot gradedqualityAmaintenanceProvides AI agents an auditable memory layer with provable deletion via signed certificates, a tamper-evident hash-chained audit trail, and bi-temporal time-travel recall over SQLite or Postgres.57 PyPIApache 2.0
TDQS
Scored across 8 tools
Most tools have distinct purposes, but context_assemble and memory_checkout overlap in functionality since checkout wraps assembly. memory_feeling_of_knowing is clearly experimental and distinct. Descriptions guide usage, preventing major confusion.
Naming is inconsistent: most tools start with 'memory_', but context_assemble does not. Verbs and nouns are mixed (e.g., memory_append vs memory_capabilities), and context_assemble uses noun_verb order instead of verb_noun.
8 tools is appropriate for a memory management system. Each tool covers a core operation (append, invalidate, query, feedback, capabilities, prediction, assembly), without being excessive or sparse.
The tool set covers the memory lifecycle: add (append), retrieve (checkout/query), update (invalidate), feedback, and discovery (capabilities). Missing a dedicated delete tool, but invalidate handles temporal updates. Minor gaps, but core workflows are supported.