ctx-memory
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Alternatives to ctx-memory
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- AlicenseAqualityBmaintenanceProvides persistent, searchable memory for AI agents across any MCP-compatible client, storing project context, user preferences, and session learnings locally in SQLite with tools to save, retrieve, search, and manage them.125 npmMIT
- FlicenseNot gradedqualityBmaintenanceEnables agents to store conversational turns in a single SQLite store and recall relevant context through lexical, entity, dense, and recent views without an LLM in the recall loop. It exposes MCP tools for remembering, bulk ingest, recall, stats, and session deletion, with persistent indexes and zero-token maintenance.-
- AlicenseAqualityDmaintenanceProvides persistent, inspectable memory storage for AI agents using SQLite. Agents can store, recall, and search memories across sessions via three MCP tools.3MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to store, retrieve, and manage persistent memories locally via an MCP server with hybrid vector and keyword search, plus tools for memory CRUD, search, backup, and import.MIT
- AlicenseNot gradedqualityBmaintenanceEnables MCP clients to give agents durable long-term memory by exposing remember, recall and forget tools backed by a typed SQLite store, so facts about a user can be written deliberately and the most important ones retrieved on request.27MIT
- AlicenseCqualityAmaintenanceProvides persistent, local-first AI memory across sessions via MCP tools for storing, searching, and retrieving context from past interactions.31962 PyPI1MIT
TDQS
Scored across 7 tools
Most tools have distinct purposes: remember (write), recall (keyword search), forget (delete), save_handoff (session summary), list_projects, export_markdown. The main overlap is get_context vs recall (both retrieve memories) and remember vs save_handoff (both persist), but descriptions make the boundaries clear enough to avoid most misselection.
All names are verb-first and lowercase, with verb_noun forms (get_context, save_handoff, list_projects, export_markdown) alongside single-verb forms (remember, recall, forget). The mix is minor and still highly readable and predictable.
Seven tools is well-scoped for a memory server, covering the core write/read/delete/list/export surface without redundancy. Each tool earns its place.
Covers the full lifecycle: write (remember, save_handoff), read (get_context, recall), delete (forget), plus list_projects and export_markdown. Minor gaps exist (no update/edit of an existing memory, no get-by-id), but these are workable via forget+remember.