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Recall by Polign

Recall by Polign

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    Provides AI agents with a persistent long-term memory over a single SQLite file, letting them write, screen, consolidate, and recall notes across sessions without any generative LLM in the loop. Recall judges relevance, follows links between notes, and signals when memory is insufficient, so agents get one to three useful facts per question instead of a generic top-k list.
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    Local memory for AI agents in one SQLite file on your own machine. Facts carry a validity window and a confidence score, so an outdated one is superseded and downweighted rather than deleted, and retrieval fuses BM25, vector similarity and a knowledge graph.
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    Gives AI agents governed, provenance-tagged memory where facts are invalidated rather than deleted and every recall result carries validity dates, confidence, and replacement links. Stores memory in a local SQLite file with tools for remembering, recalling, invalidating, and pinning facts, plus policy enforcement and an audit trail.
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    Open-source AI memory layer for LLM agents. Importance scoring, temporal decay, hierarchical memory (facts, summaries, themes), YMYL prioritization, and active retrieval with contradiction detection. Supports OpenAI, Anthropic, Ollama. Local-first with SQLite + FAISS.
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    Integrates an Engram brain with Claude Code via MCP, providing tools for searching, retrieving, and adding memories.
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    Enables AI agents to store decisions as a versioned history, linking each new decision to the one it replaces so that recall always resolves to the decision currently in force instead of obsolete ones. It runs fully locally on a single SQLite file with BM25 search, and can optionally detect replacements automatically via an LLM or heuristic linker.
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    Persistent semantic memory for AI agents. SQLite-backed, local-first, zero config. Semantic search via Ollama embeddings with keyword fallback. Tools: remember, recall, history, forget, stats.
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    Cross-agent memory server: hybrid (vector + full-text + knowledge-graph) recall, per-user private/shared visibility, write-side secret/PII redaction, and as-of-date bi-temporal fact queries. Auto-injection hooks for Claude Code / Cursor / Codex; self-hostable on PostgreSQL or SQLite.
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    Audit-grade memory backbone for agent teams. Bi-temporal facts (event time + transaction time, with recall(as_of=...) replay), 6-step deterministic retrieval (no LLM in the critical path), conversation ingest with speaker-locked dual-pass extraction, per-tenant Postgres row-level security, and Ed25519-signed provenance. Postgres + pgvector + Neo4j defaults.
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TDQS

A4.1/5.0

Scored across 5 tools

Disambiguation4/5

The five tools cover clearly different operations: storing, querying, withdrawing, tracing one item's history, and comparing beliefs across time. The only mild overlap is between recall's `since` mode and diff, which both answer 'what changed', though their descriptions differentiate instants versus periods.

Naming Consistency4/5

All names are single, lowercase words with a consistent terse style. However, remember/recall/forget are verbs while history and diff are nouns, a minor deviation from a pure verb convention.

Tool Count5/5

Five tools is well scoped for a focused memory service, with each tool earning its place across the read/write/history lifecycle. No tool feels redundant or missing from the core set.

Completeness5/5

The surface covers the full memory lifecycle: write (remember), read (recall with profile, point-in-time, and delta views), soft delete (forget), per-item history, and cross-instant diff. No dead ends are apparent for the stated purpose.

Maintenance

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