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Alternatives to engrim

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    A
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    Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.
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    Enables MCP clients to interact with pre-registered SQLite databases using aliases, supporting schema inspection, read-only queries, and data modification via tools.
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    Persistent memory for any AI assistant. Zero token cost until recall. Stores memories in local SQLite, ranks by 6-factor scoring, returns results 79% smaller than JSON. Works with Claude, ChatGPT, Grok, Cursor, Windsurf, and any MCP client.
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    Local-first, auditable memory for Codex, Claude Code, and MCP clients. It stores scoped user/project memory in SQLite or Postgres, serves read-only recall and inspection tools by default, and supports opt-in governed writeback with review and forget controls.
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TDQS

A4.2/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: context retrieval, semantic search, writing records, and pre-clear review. There is no overlap between reading curated context, searching all memory, adding new records, or checking for unsaved decisions.

Naming Consistency4/5

All tools share the engrim_ prefix and use short, consistent verb-like suffixes (context, recall, add, review). Minor deviation: 'context' and 'recall' are nouns/verbs rather than a strict verb_noun pattern, but the naming is predictable and readable.

Tool Count5/5

Four tools is a well-scoped set for a memory server: read curated context, search all memory, write new memory, and review unsaved history. Each tool earns its place with no redundancy.

Completeness4/5

The core memory lifecycle is covered: add, recall, context, and pre-clear review. A minor gap is the lack of explicit update/delete operations for correcting or removing stale records, but agents can work around this by adding superseding records.

Maintenance

ActivityMaintained
ResponsivenessNo issues