Spomory
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- FlicenseNot gradedqualityCmaintenanceEnables AI coding agents and IDEs to capture conversations, extract structured knowledge into a queryable graph database, and recall past decisions, patterns, files, and errors across all projects and workspaces. Provides persistent memory tools for saving, searching, and cleaning up knowledge via MCP.2-
- FlicenseNot gradedqualityAmaintenanceEnables Claude Code to maintain cross-session memory by adding, searching, updating, and deleting stored information through MCP tools, backed by self-hosted Qdrant and optional Neo4j knowledge graphs with Ollama or Anthropic as the LLM.-
- FlicenseNot gradedqualityAmaintenanceEnables Claude Code to maintain persistent cross-session memory using self-hosted Qdrant, Neo4j, and Ollama, with optional Anthropic or local LLM backends, and exposes MCP tools for adding, searching, updating, deleting, and graphing memories.-
- FlicenseNot gradedqualityAmaintenanceEnables Claude Code to run a self-hosted persistent memory server backed by Qdrant, Neo4j, and Ollama, exposing 11 MCP tools for adding, searching, updating, deleting, and organizing memories and knowledge-graph entities. Supports Anthropic or local Ollama LLMs, automatic session hooks, and cross-session memory management.-
TDQS
Scored across 6 tools
Each tool targets a clear, distinct operation: add, graph lookup, semantic search, single-fact delete, full wipe, and export. The two delete tools are explicitly differentiated by scope, and get_graph vs search_memory are distinguished by input type (entity vs natural-language query) and output format.
All tool names follow the same lower_snake_case verb_noun pattern: add_, get_, search_, forget_, forget_all_, export_. The shared 'memory' base and the obvious 'forget_memory' / 'forget_all_memory' pair make the naming highly predictable.
Six tools is a well-scoped size for a memory-graph server, covering creation, retrieval, deletion, and export without redundancy or bloat. Each tool earns its place and the count sits comfortably in the ideal 3–15 range.
The core memory lifecycle is covered: add, retrieve (graph and semantic), delete single, delete all, and export. Minor gaps exist—there is no explicit update operation and no import counterpart to the export—but agents can work around these via add_memory and re-adding facts.