Recall by Polign
OfficialRelated Servers
Alternatives to Recall by Polign
- AlicenseAqualityBmaintenanceProvides 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.11146 PyPI4MIT
- AlicenseNot gradedqualityBmaintenanceSelf-hosted long-term memory for AI agents on your own Postgres. Facts are dated, versioned and superseded rather than silently overwritten, every recall ships with an inspectable trace, and agents can correct wrong memories from inside the conversation.2Apache 2.0
- AlicenseNot gradedqualityBmaintenanceLocal 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 Facts carry a validity window and a confidence score, so an outdated one is superseded and downweighted rather than deleted, and retrieval fuses BM25, vector similarity and a knowledge graph.3Business Source 1.1
- AlicenseNot gradedqualityBmaintenanceGives 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.137 npm3Apache 2.0
- AlicenseNot gradedqualityBmaintenanceOpen-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.14 PyPI50Apache 2.0
- AlicenseNot gradedqualityDmaintenanceIntegrates an Engram brain with Claude Code via MCP, providing tools for searching, retrieving, and adding memories.17 npmMIT
Related Servers
- AlicenseBqualityBmaintenanceEnables 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.5MIT
- AlicenseAqualityCmaintenanceEnables coding agents to save facts, decisions and conventions into a single SQLite file and search them again in later sessions. Recall is ranked by BM25 relevance boosted by recency and scoped per project, with zero native dependencies.4MIT
- AlicenseAqualityCmaintenancePersistent 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.1737 npm1MIT

Loreofficial
AlicenseBqualityCmaintenanceCross-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.4639 PyPI10MIT- AlicenseNot gradedqualityCmaintenanceAudit-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.37 PyPI14MIT
TDQS
Scored across 5 tools
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.
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.
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.
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.