hive-memory
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Alternatives to hive-memory
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- FlicenseAqualityBmaintenanceShared fleet memory for AI agents — what one agent learns, the whole fleet knows. Nightly self-correction: stale facts rewritten in place, duplicates merged. Recall pushed into every prompt in supported coding agents. Self-hosted.113-
- AlicenseNot gradedqualityAmaintenanceProvides persistent memory for AI agents via MCP, enabling agents to store and access notes, files, and session context across sessions and clients while under user control.4MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to store, search, assemble, and manage local-first memories through seven MCP tools, including conversation turns, feedback, status, and dashboard access without cloud dependencies.AGPL 3.0
- AlicenseCqualityAmaintenanceProvides AI agents with a human-inspired memory layer via MCP, enabling episodic and semantic memory recall, forgetting curves, consolidation, and contradiction detection. It integrates with MCP clients to offer local-first, dependency-free memory management.981MIT
- FlicenseNot gradedqualityAmaintenanceEnables MCP-compatible coding tools to share a portable, local-first AI work identity and memory layer, so preferences, decisions, lessons, and project context persist across sessions and clients. Users can inspect, edit, approve, and override what the AI receives, keeping the store on their own machine without a cloud account.-
- AlicenseNot gradedqualityCmaintenanceEnables multiple AI agents and clients to share a self-hosted memory store over MCP or REST, supporting note creation, search, change tracking, and optional semantic retrieval from desktop, web, or mobile.MIT
TDQS
Scored across 6 tools
Each tool has a clearly delineated role, and the descriptions actively resolve boundary cases (recall vs get_context vs manage list_pending; say vs board; propose vs manage). No two tools compete for the same action, so misselection is unlikely.
Names are uniformly short and lowercase, but the style is slightly mixed: mostly bare verbs (recall, propose, manage, say) alongside a verb_noun (get_context) and a bare noun (board). It remains readable and predictable in tone, just not a strict single pattern.
Six tools cleanly cover the memory lifecycle plus agent communication, with no redundant or filler entries. Each tool earns its place for a focused memory server.
Full read/create/pending-inspect/soft-delete/restore lifecycle is present, plus session bootstrap and a messaging channel; no dead ends in the core flow. The one visible gap is revising the content of an already-confirmed memory (only forget/restore, not edit), which agents must work around via propose.