Why this fit
Teams evaluating AI models, assistants and generative workflows, particularly database workflows, search and retrieval — source available on GitHub.
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Catalogue record
github.com
vestige
⭐ 605 — Local-first cognitive memory MCP server for coding agents; SQLite store, FSRS-6 retention, prediction-error gating, active forgettin...
Checked Oct 27, 2026Evidence completeness: evidenceREADME refreshed Oct 16, 2026
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⭐ 605 — Local-first cognitive memory MCP server for coding agents; SQLite store, FSRS-6 retention, prediction-error gating, active forgetting, spreading activation, hybrid retrieval, and provenance/correction tools. Single Rust binary with a 3D dashboard. Works with Claude Code, Cursor, VS Code, Codex, Windsurf, and JetBrains. AGPL-3.0.
Best for
Teams evaluating AI models, assistants and generative workflows, particularly database workflows, search and retrieval — source available on GitHub.
Known limitations
Workflows that require fully deterministic, auditable outputs with no human review step.
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Evidence summary
Known limitations
Workflows that require fully deterministic, auditable outputs with no human review step.
Catalogue confidence
Catalogue data checked Oct 27, 2026.
GitHub-backed record with source-attributed context.
Repository context
Vestige
GitHub / samvallad33/vestige
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