Score7.7
Popularity88.0
Riskconditional
TierSilver
Score breakdown
Usefulness8.0
Novelty9.0
Momentum7.0
Maturity7.4
Open-source/build8.4
Evidence8.0
Workflow potential9.2
Setup ease8.8
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for AI agent authors who want a **local-first** memory substrate that runs on a single SQLite file with FTS5 search — no vector store, no embeddings, no retrieval model, no external infrastructure — and the agent runs on a 4 vCPU / 16 GB box; for engineering teams that need **multi-tenant by design** — the schema enforces `UNIQUE (tenant_id, category, name)` at the SQLite level so two
Who should use it
AI agent authors who want a **local-first** memory substrate that runs on a single SQLite file with FTS5 search — no vector store, no embeddings, no retrieval model, no external infrastructure — and the agent runs on a 4 vCPU / 16 GB box Engineering teams that need **multi-tenant by design** — the schema enforces `UNIQUE (tenant_id, category, name)` at the SQLite level so two agents cannot stomp each other's WARM entities Engineering teams that need a **rule-enforced single source of truth per entity** — Rule 43 is enforced at the schema level, not just by convention in the application code, and drift is impossible by construction Engineering teams that want **append-only audit trail** — the COLD journal tier is append-only by schema, ARCHIVE keeps retired entities for audit, REFERENCE is for static knowledge that rarely changes, HOT is the live working state rewritten in place **Hermes Agent v0.13+** users — `pip install sibyl-memory-hermes && sibyl-memory-hermes install-plugin` and edit `~/.hermes/config.yaml` with `memory: {provider: sibyl}` MCP-compatible agent users (Claude Code, Codex, Cursor, Continue) — `pip install sibyl-memory-mcp` and point any MCP client at the bundled server entry point Users who care about **privacy disclosure** — the README is explicit that memory content never leaves the machine, the only outbound network call is tier verification (account id, session token, DB byte size, proposed delta — never the memory contents), and free unactivated use makes no network calls at all Engineering teams evaluating research-vs-production — the 95.6% LongMemEval Oracle score is self-reported and the blog explicitly notes 'no official leaderboard exists, judges and generator models vary across entries,' but the architecture is the only file-based system in the top tier of the community leaderboard Engineering teams that want a **linter** to surface common architectural smells (unbounded HOT writes, duplicate WARM entities) — the memory linter is part of the activated path **Vendor-API-key-prerequisite caveat (cycle 164 pattern)**: the **free, unactivated path** makes no network calls and runs entirely local — this is the right starting surface for evaluation; the **activated path** binds a wallet or email and writes credentials to `~/.sibyl-memory/credentials.json`; the **staker / subscription tiers** unlock self-learning skill detection, the memory linter, and remove the local cap; if you need those features the OSS substrate is clean MIT but the activated path Evaluation: `pip install sibyl-memory-cli && sibyl init` is the install path; for the Hermes Agent integration: `pip install sibyl-memory-hermes && sibyl-memory-hermes install-plugin`; for direct SDK use: `pip install sibyl-memory-client`; for MCP exposure: `pip install sibyl-memory-mcp`; the free unactivated tier is the right starting surface
Who should skip it
Skip Sibyl-Labs/Sibyl-Memory unless the captured evidence suggests it solves a problem you are actively working on.
About this signal
Sibyl-Labs/Sibyl-Memory is tracked by RepoRadar as an AI project in the MIT local-first agent-memory family section. First seen 2026-06-25; the source record was last checked on 2026-06-25. The current verdict is 'try now' with a Silver tier and easy setup difficulty. Across RepoRadar's eight signals, Sibyl-Labs/Sibyl-Memory is strongest on workflow potential (9.2) and novelty (9.0) and weakest on momentum (7.0) — a profile worth weighing against your own priorities. This page summarizes the public evidence on the linked source page and states where additional review is still needed.
How this item is evaluated
The Sibyl-Labs/Sibyl-Memory record combines a 7.7/10 composite score with separate popularity (88.0), risk (conditional), and setup (easy) signals. See the scoring methodology for the current weights and evidence definitions.
Risk explanation
free unactivated path makes no network calls; activated path binds a wallet or email to ~/.sibyl-memory/credentials.json and uses a vendor-controlled tier-check endpoint at api.sibyllabs.org; staker/subscription tiers required for self-learning skill detection; memory linter.
Evidence links
Closest alternatives / related signals
sibyl-memory sibyl-labs local-first sqlite fts5 no-vectors no-embeddings no-retrieval-model