shared-memory
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Alternatives to shared-memory
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Related Servers
- AlicenseNot gradedqualityDmaintenanceSelf-hosted semantic memory for AI agents. Save worklogs, decisions, and notes via MCP, then recall them across sessions by meaning rather than keyword. Backed by Postgres + pgvector with local embeddings (multilingual-e5-base).1MIT
- AlicenseNot gradedqualityDmaintenanceA portable self-hosted memory layer for AI tools, storing context, memories, and handoffs for access from any MCP-compatible client.15 npmMIT
- AlicenseNot gradedqualityCmaintenanceA semantic memory store for AI agents, enabling persistent memory across sessions via MCP tools with semantic search, scoped access, and local embeddings.MIT
- AlicenseNot gradedqualityDmaintenancePersistent, searchable memory for AI agents over the Model Context Protocol, enabling memory storage, full-text search with BM25 ranking, and retrieval across sessions.6 npmMIT
- FlicenseNot gradedqualityDmaintenanceFree, persistent memory layer for AI agents, enabling storage and semantic search of memories via MCP or REST.-
- AlicenseAqualityCmaintenancePortable cognitive memory for AI agents with semantic search, decay, and deduplication.819 npm2MIT
TDQS
Scored across 5 tools
Each tool maps to a distinct lifecycle operation on a single resource: add, search, update, forget, stats. There is no meaningful overlap — search retrieves, stats aggregates, and the write operations are cleanly separated.
All five tools follow a strict memory_<verb> snake_case pattern with clear, conventional verbs (add, search, update, forget, stats). No mixed conventions or vague names.
Five tools is a tight, well-scoped surface for a memory store: write, read, mutate, delete, and observe. Every tool earns its place with no redundancy or filler.
The set covers the full CRUD lifecycle plus stats, and search likely substitutes for a direct get-by-id. Minor gaps remain around bulk operations and explicit id-based retrieval, but core workflows are covered without dead ends.