Engram Alpha
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Alternatives to Engram Alpha
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Related Servers
- AlicenseAqualityCmaintenanceEnables coding agents to share a persistent local memory store across sessions and clients, saving, searching, updating, and retrieving facts, decisions, incidents, preferences, references, and snippets with semantic and lexical search.10MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to save, recall, and forget persistent memories stored entirely on the local machine in SQLite, using hybrid semantic and keyword search with on-device embeddings, plus spaces and profile context injection.MIT
- FlicenseNot gradedqualityAmaintenanceEnables AI coding agents to store and retrieve persistent project and cross-project memories via semantic search, so decisions, preferences, error patterns, and guidelines survive across sessions. Optionally supports autonomous task execution built on the same local-first knowledge store.-
- AlicenseNot gradedqualityAmaintenanceProvides AI coding agents with a persistent memory layer to save, recall, update, and track memories across sessions and repositories using hybrid semantic search.6MIT
- AlicenseNot gradedqualityAmaintenanceProvides persistent, local-first memory with knowledge graph and hybrid search for AI coding agents, reducing token usage by storing decisions, patterns, and codebase context.41 PyPI9MIT
- FlicenseNot gradedqualityAmaintenanceEnables AI coding agents to read and write persistent memory directly during sessions, storing decisions, preferences, error patterns, research, and cross-project guidelines in local SQLite databases. Supports semantic search so relevant project and global context can be recalled by meaning, fully offline and without API keys.-
TDQS
Scored across 15 tools
Most tools have distinct targets: memory nodes, graph relations, ingestion, maintenance, and stats. A few pairs like save_memory vs extract_and_save_memory or search_memory vs auto_context could overlap, but their descriptions clarify the intended workflow. No tools are truly redundant.
Tool names are consistently lowercase snake_case and mostly follow a verb-first pattern. The main outlier is auto_context, which is a noun phrase, and graph-related names mix save_graph_relation, query_graph, and visualize_graph. Overall the pattern remains predictable and readable.
15 tools is at the upper edge of ideal but well-scoped for a memory system that combines vector storage, knowledge graph operations, ingestion, reflection, and maintenance. Each tool serves a distinct purpose, and none feel purely decorative or redundant.
Memory CRUD is well covered with save, search, edit, delete, and list, and graph relations have save and query support. Missing direct graph relation editing/deletion and a get-memory-by-ID tool are minor gaps, but cascade deletion and search/list provide workarounds.