LedgerMem MCP Serverofficial
A
licenseNot graded
qualityB
maintenanceEnables persistent memory storage and retrieval for MCP clients, allowing AI assistants to remember facts and context across conversations.
467 npm
MIT
khwan-mcp
Officialby khwanlabs
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TDQS
A4.5/5.0
Scored across 6 tools
Disambiguation4/5
The tools split into two semantically overlapping pairs—prepare/recall for retrieval and record/remember for persistence—but the descriptions clearly separate turn-by-turn context from session seeding, and structured recording from standalone fact storage. khwan_memory and khwan_cores are unambiguous. An agent must read carefully, but misselection risk is low.
Naming Consistency4/5
All tools share the khwan_ prefix and use lowercase snake_case, with most names being imperative verbs: prepare, record, recall, remember. khwan_memory and khwan_cores break the verb pattern by being plain nouns, making the set slightly inconsistent but still readable and predictable.
Tool Count5/5
Six tools is a well-scoped size for a memory/context server: two for the turn loop, one for session seeding, one for direct persistence, one for debugging, and one for core isolation. Each tool has a clear job and none feels redundant.
Completeness3/5
The core memory lifecycle is covered: prepare/record for turns, remember for durable facts, recall for retrieval, and memory for inspection. However, there is no explicit forget/update or memory-editing tool, which is a notable gap for a persistent brain, though it does not break the main workflows.
Maintenance
ActivityMaintained
ResponsivenessNo issues