membrain
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- AlicenseNot gradedqualityAmaintenanceEnables AI agents to keep durable long-term memory on the user's own machine, writing sessions and messages into a local SQLite database and retrieving them via keyword, exact, or optional semantic search with surrounding context. Runs entirely offline over stdio, so no cloud service or API key is required to give an agent recall across sessions.1MIT
- AlicenseNot gradedqualityBmaintenanceWraps a dependency-free memory lifecycle engine as six read-only MCP tools, letting any agent extract facts with pure regex, score signals, compute Ebbinghaus decay and archival judgments, and simulate a full five-stage dream cycle for long-term memory growth. Runs over stdio or streamable HTTP with no API key, storing no caller data.1MIT
- AlicenseAqualityCmaintenanceEmbedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.743Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables agents to store and retrieve hierarchical memory in cryptographically partitioned namespaces, with HMAC-based isolation and Ebbinghaus time-decay so recall fades realistically over time. Runs as a zero-dependency Python STDIO MCP server that returns deterministic JSON results.7MIT
- AlicenseBqualityCmaintenanceExposes 12 memory and multi-agent tools over stdio JSON-RPC so agents can write episodes and extracted facts, then recall them with hybrid retrieval, bi-temporal state tracking, and evidence-chain decomposition under a token budget. It also supports agent registration, team-shared memory with access grants, and an event bus for multi-agent collaboration.12Apache 2.0
- AlicenseNot gradedqualityAmaintenanceEnables multiple AI agents to share a self-hosted, namespace-scoped cloud memory via a local stdio MCP server that caches valid results locally in SQLite and syncs to a remote MySQL backend. Exposes tools for searching, retrieving, timeline browsing, remembering, forgetting, and syncing memories with versioning, conflict handling, and redaction.Apache 2.0
TDQS
Scored across 5 tools
Each tool has a distinct role: remember writes, recall searches, brief returns a curated wake-up subset, tick runs maintenance, stats reports metrics. The only mild overlap is between recall and brief (both return memories), but the descriptions clearly separate query-driven retrieval from a fixed high-importance digest.
All five names are short, lowercase, single-word tokens with no mixed casing or prefix conventions. There is a slight verb/noun mix (remember/recall/tick vs. brief/stats), but the style is uniform and readable.
Five tools cleanly cover the memory lifecycle: write, retrieve, digest, maintain, and measure. Nothing feels redundant and no operation is split into artificial variants.
The core write/read/maintenance loop is covered, but there is no way to update or delete a specific memory — errors can only be corrected by writing a new memory or waiting for tick decay. This append-only design is plausible but leaves notable gaps for agents needing correction or targeted removal.