engram-global
Related Servers
Alternatives to engram-global
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityDmaintenanceAn MCP server that provides AI agents with persistent, multi-layered memory inspired by the human brain, including consolidation, self-reflection, and generative replay.1MIT
- AlicenseNot gradedqualityDmaintenanceA self-hosted MCP server that gives AI agents persistent, searchable memory with importance scoring, knowledge graphs, and autonomous memory consolidation.1MIT
- AlicenseNot gradedqualityBmaintenanceMCP server that gives AI agents persistent long-term memory, storing and recalling facts, decisions, errors, procedures, and episodes across sessions.38 npm5Apache 2.0
- AlicenseNot gradedqualityBmaintenanceMCP server that gives AI coding agents persistent memory across sessions, storing architecture decisions, past bugs, and codebase conventions locally.5 npmMIT
- AlicenseAqualityBmaintenanceThis MCP server enables AI agents to store memories with sensory fingerprints and automatically surface relevant recollections when incoming cues such as location, time, text, images, or audio align, alongside explicit recall and forgetting tools.4787 PyPIApache 2.0
- AlicenseAqualityDmaintenanceMCP server providing persistent memory for AI agents, enabling them to read, write, and query memories across sessions.915 npmMIT
TDQS
Scored across 11 tools
Each tool has a clearly distinct purpose: remember saves, recall searches, forget soft-deletes, correct replaces erroneous memories, reinforce boosts relevance, link creates explicit connections, consolidation_candidates and skill_candidates surface different cluster types, mark_consolidated finalizes consolidation, reindex rebuilds the index, and stats reports metrics. Even the superficially similar candidates tools are well-differentiated by their described use cases.
Naming uses a mix of simple verbs (remember, recall, forget, reinforce, correct, link, reindex), a noun (stats), and underscore-separated phrases (consolidation_candidates, skill_candidates, mark_consolidated). The convention is not uniform, but names are still readable and descriptive enough to infer their functions.
With 11 tools, the server is well-scoped for a comprehensive memory management system. Each tool addresses a distinct lifecycle phase (creation, retrieval, correction, reinforcement, linking, consolidation, maintenance, and statistics), and none feel redundant or missing.
The tool surface covers the core memory lifecycle (create, read, soft-delete, correct, reinforce, link, consolidate, extract skills) plus maintenance and stats. Minor gaps exist, such as no direct update tool for editing a memory's content or a restore-from-trash operation, but these are workaroundable and the provided workflow is intentional.