cognitive-harness-mcp
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AlicenseNot gradedqualityAmaintenanceEnables AI agents to persist, recall, expand, trace, and inspect durable memories with provenance through MCP tools.MIT- AlicenseNot gradedqualityAmaintenanceProvides AI agents with persistent, human-like memory infrastructure via MCP, enabling them to store, search, summarize, and forget episodic, semantic, procedural, and working memories across sessions.1,203 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to store and semantically retrieve durable memories across sessions via MCP or REST, with tools for remembering, recalling, asking, updating, and forgetting memories.12 npmMIT
- AlicenseNot gradedqualityBmaintenanceProvides long-term memory for AI agents via MCP tools to store, recall, and delete memories, with per-user scoping and usage limits.AGPL 3.0
- AlicenseNot gradedqualityCmaintenanceEnables agents to store, recall, and manage persistent memory documents through MCP tools, with authenticated context tokens and hybrid lexical/vector search.MIT
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TDQS
Scored across 7 tools
Each tool targets a distinct operation: search, list, stats, summary, write, update, and forget are clearly separated by purpose. Search and list both retrieve memories but are differentiated by query-based filtering versus chronological browsing.
All tools share the cognitive_ prefix and mostly use verb-style names like cognitive_search, cognitive_write, and cognitive_update. The pattern is slightly weakened by noun-style names cognitive_stats and cognitive_summary, but the convention remains highly predictable.
Seven tools is well-scoped for a memory management server: full CRUD plus search, statistics, and aggregated summary. Each tool earns its place without redundancy or bloat.
The tool surface fully covers the memory lifecycle: write, read via search/list/summary, update, and forget with both degrade and delete modes. The addition of stats and summary fills retrieval and introspection needs, leaving no obvious gaps.