Changelog

Full version history for VEKTOR Slipstream from v1.0.0 to v1.6.3. Eleven releases covering initial SQLite persistence, hardware-accelerated hybrid recall, MAGMA causal graphs, FadeMem intelligence architecture, MCP connector layer, provider-agnostic LLM, CLOAK stealth browsing, SSH deployment tools, JOT synthesis mode, and stability fixes.

v1.6.3

FadeMem Intelligence Architecture — Layers 0–6

Full implementation of the FadeMem decay architecture (arXiv:2601.18642, Feb 2026) and Adaptive Budgeted Forgetting (arXiv:2604.02280, Apr 2026) into the VEKTOR memory pipeline. To our knowledge the first production SDK implementation of either paper.

• Layer 0 — Pre-ingest signal filter (vektor-intake.js): NER/verb density scoring, source trust matrix (15 source types × 4 actor types), bot signature detection. Drops structural noise before any DB write.
• Layer 1 — Dual-tier memory (LML/SML): importance_score, memory_layer, strength columns. Initial importance computed from FadeMem formula I = 0.4×rel + 0.3×freq_sat + 0.3×recency after embedding, scored against standing query vectors.
• Layer 2 — Adaptive decay (vektor-decay.js): Stretched exponential v(t) = v(0) × exp(-λ × t^β), β=0.8 LML / 1.2 SML. Causal decay suppression via trigger-cached max_child_importance. Access reinforcement with diminishing returns. LML half-life ~11d, SML ~5d.
• Layer 3 — Conflict resolution (vektor-conflict.js): Five-verdict AUDN upgrade (COMPATIBLE, CONTRADICTORY, SUBSUMES, SUBSUMED, NO_OP). 2D trust matrix prevents automated sources suppressing human ones.
• Layer 4 — Memory fusion (vektor-fusion.js): LLM-guided cluster consolidation during REM cycle. Variance-boosted strength on fused nodes. Source memories moved to cold storage.
• Layer 5 — Budgeted pruning (vektor-prune.js): Knapsack pruning with sub-linear token cost sqrt(tokens). Per-source node limits enforced at sync time. Source budget table seeded at migration.
• Layer 6 — Additive reranking (vektor-recall-ranked.js): Composite score 0.5×sim + 0.2×strength + 0.15×importance + 0.15×causal_weight applied as final pass after cross-encoder rerank.

Schema Migration 162 — 21 New Migrations

migrate-162.js: importance_score, memory_layer, strength, access_count, last_decay_calc, decay_rate, source_type, actor_type, trust_score, max_child_importance, cold_storage, cold_at. Tables: vektor_cold_storage, vektor_standing_queries, vektor_source_budgets, vektor_sync_cursors, vektor_sync_health. Three SQLite triggers maintaining causal cache on importance changes and edge insert/delete.

MCP Connector Layer

vektor-mcp-reader.js and vektor-connector-base.js: MCP stdio connector pipeline syncing external tools into VEKTOR memory. Filesystem and GitHub connectors added to setup wizard Step 10. GitHub connector uses dedicated fetchGithubItems strategy (list_issues, list_commits, list_pull_requests) with owner/repos from wizard config. Staggered ingestion (5ms between writes, 200-item cap per run). Sync cursor table prevents re-scanning history.

Provider-Agnostic LLM

vektor-llm-provider.js: All 15 wizard providers supported (groq, claude, openai, gemini, mistral, deepseek, together, cohere, xai, minimax, nvidia, perplexity, lmstudio, litellm, ollama). Reads user config — no hardcoded API keys. Replaces Groq hardcoding in vektor-conflict.js, vektor-fusion.js, vektor-standing.js, vektor-sleep.js.

Standing Queries — Auto-Evolving Context

vektor-standing.js: Weekly synthesis from top-15 LML memories via configured LLM provider. Goal statements embedded with local model and stored as vectors. Used as rel component in FadeMem importance scoring for background syncs. 14-day TTL.

Graph Visualisation Fix

vektor-graph-server.js: ns namespace variable undefined in apiGraph() SQL handler caused all graph API calls to return {ok: false, error: "ns is not defined"}. Graph UI showed spinner indefinitely. Fix: extract ns from URL params before SQL clause construction.

REM Cycle

vektor-sleep.js: Orchestrates decay → fusion → prune → standing in sequence. All apiKey guards removed — provider config used instead. REM cycle confirmed at 716ms on 17,523-node graph.

Causal Inference Engine — Four-Phase, Zero Dependencies

Full causal reasoning layer deployed to src/causal/. Node ≥18 required, no external dependencies.

• Phase 1 — G-Formula estimator (gformula-estimator.js) — ATE identification and estimation using the G-computation formula over the MAGMA causal graph.
• Phase 2 — MSM / IPW estimator (msm-estimator.js) — Marginal structural model estimation via inverse probability weighting, handling time-varying confounders across memory timelines.
• Phase 3 — IV Bounds estimator (iv-bounds-estimator.js) — Instrumental variable partial identification bounds (Manski-style) for causal effect estimation when unobserved confounders are present.
• Phase 4 — Root Cause Analysis Engine (vektor-rca-engine.js) — Combines all prior phases to build an intervention graph, trace agent failures backwards through the causal chain, score root causes by impact, and predict fix outcomes.

CLI test harness (cli-test.js) ships with --verbose and --phase flags for targeted phase testing. 31 tests passing across all four phases.

DeepFlow v2 — Deterministic 8-Step Pipeline

The vektor.mjs deep agent path (deep:true) has been rebuilt as a fully deterministic pipeline, replacing the prior unbounded loop. Pipeline stages: DECOMPOSE → VAULT-FIRST → SWEEP → LOCI → COMMIT → ADVERSARIAL → SYNTHESISE → CRITIC+PATCH. Three new tools added: adversarial_search, loci_rank, and patch. DeerFlow renamed to DeepFlow throughout. The /agent path (deep:false) is unchanged. A full syntax repair pass was applied — BOM removal, optional chaining and nullish coalescing fixes, stray markdown commented out.

JOT Collab — Two-Pass Article Generation

Groq LLaMA two-pass generation system integrated into the JOT SDK: rate-limit handling with automatic backoff, API key rotation across multiple Groq keys, APA7 citation infrastructure, and a post-generation citation scanner. Full bug audit of four core JOT files with critical fixes applied via fix-criticals.js. JOT v1.5.x additions also included: TAG pill and /api/ai/transform tag prompt (v1.5.2), notes RAG wired into /api/memory/think, vektor ask libuv Windows assertion crash resolved (v1.5.7), and lightbulb indicator overlap fix (v1.5.8).

Download Server — Version Mount Fix

The licence-gated download endpoint was serving vektor-slipstream-1.5.8.tgz despite the tarball at ~/downloads/ and ~/vektor-monorepo/releases/ being updated to v1.6.3. Root cause: PM2 bakes environment variables into the process at launch time. dotenv does not override variables already present in process.env, so updating .env and running pm2 restart --update-env both silently preserved the stale VERSION_SLIPSTREAM=1.5.8 value. Fix: delete the PM2 process and re-register with the version passed explicitly at start time, then pm2 save to persist. Affected service: vektor-server (vektor-monorepo).

better-sqlite3 — Bundled Binary (Windows)

better-sqlite3 moved from optionalDependencies to dependencies with a pre-built Windows binary bundled under bundled/better-sqlite3/build/Release/. Eliminates the npm rebuild requirement on Windows installs where native build toolchains are absent. The loader uses process.chdir() before requiring the native module so the relative path resolution is correct regardless of working directory. postinstall.js silently skips the rebuild step when the bundled binary is present.

sqlite-vec — ANN Recall Wired

sqlite-vec upgraded to ^0.1.9. The vec_memories virtual table schema is now created on DB init and the write path stores quantized float32 vectors alongside the BM25 FTS5 index. Recall falls back gracefully to cosine scan if sqlite-vec fails to load (e.g. architecture mismatch). ANN nearest-neighbour swap replaces full cosine scan for large graphs (>5,000 memories), reducing p95 recall latency by ~60%.

MAGMA Graph — vektor_status and vektor_related Tools

Two new MCP tools shipped in the CLOAK layer:

• vektor_status — lightweight memory health check returning memory count, namespace, last store timestamp, and embedder mode. Designed for session auto-probe without triggering a full recall pass.
• vektor_related — traverses memory graph edges for a specific memory ID, returning typed neighbours (semantic / causal / temporal / entity) up to N hops. Replaces manual memory.graph() calls in agentic workflows.

Bug Fix — Percept isOnTopic Threshold

The Percept Chat Layer was firing topic-match hints too aggressively. The isOnTopic cosine score threshold was lowered from 0.35 to 0.25, reducing false-positive interruptions during tangential conversation turns. Affected module: vektor-percept-chat.js.

Bug Fix — vektor rem (memory.dream() removed)

The npx vektor rem CLI command was calling memory.dream(), a method removed in v1.5.4. The command now uses memory.stats() to retrieve fragment counts and memory.recall() to seed the compression pass, matching the current API surface. Affected module: vektor.mjs.

Infrastructure — GUI API Proxy Routes

Relative /api/memory/* calls from vektor-graph-ui.html were hitting the wrong server when the GUI was served from a non-default port. Proxy routes added to the local graph server so all /api/memory/think and /api/memory/remember calls resolve correctly regardless of serving context. Affected module: vektor-graph-server.js.

v1.5.8

Integration Guide Expansion

The Integration Guides page has been expanded from 9 to 21 documented integrations — every provider and tool listed on the Downloads page now has a dedicated guide with config snippet and notes.

New Provider Integrations

Full setup guides added for:

• LiteLLM Proxy — point VEKTOR at any LiteLLM proxy endpoint; zero code changes, provider-agnostic switching.
• LM Studio — fully offline memory via LM Studio's OpenAI-compatible local endpoint.
• NVIDIA NIM — near-local inference latency with automatic failover routing to Anthropic or OpenAI.
• MiniMax — abab6.5s for high-volume batch summarisation; lowest cost-per-token for REM compression passes.
• DeepSeek — DeepSeek-V3 and DeepSeek-R1 via the OpenAI-compatible endpoint. No adapter required.
• xAI / Grok — Grok-3 and Grok-3-mini with persistent MAGMA memory. OpenAI-compatible API routing.
• Together AI — 200+ open models (Llama, Mistral, Qwen) with VEKTOR memory attached.
• Cohere — Command R and Command R+ paired with VEKTOR's MAGMA graph for structured RAG workloads.
• Perplexity — Sonar online models with persistent session context layered on top of live web search grounding.

New Tool & Framework Integrations

• CrewAI — Python adapter available. Drop-in VektorMemory class for CrewAI agents. Local bridge, zero cloud dependency.
• Vex — open-source memory portability CLI. Export .vmig.jsonl from VEKTOR and import to Pinecone, Qdrant, or pgvector.
• Vek-Sync — open-source MCP config sync across Claude Desktop, Cursor, Windsurf, VS Code, and Cline. AES-256 credential vault.

Percept Chat Layer

A session intelligence layer that plugs into the VEKTOR REPL and surfaces memory contextually as you work — like a colleague who remembers what you were doing. Five capabilities added to vektor-percept-chat.js:

• Morning Handover — on startup, surfaces yesterday’s active topic thread, where you left off, and any new web signals relevant to that thread.
• Progressive Idea Surfacing — accumulates a topic buffer as you type; at natural pause points surfaces 1–3 related memories as soft hints that deepen if the topic sustains.
• Step Tracker — detects multi-step tasks (code, research, trademark filing) and displays the current step inline with auto-saved progress.
• Idea Expansion — three depth levels earned by engagement: Whisper (single concept word), Bloom (short phrase + one connection), Anchor (synthesised insight, held until topic shifts). Never triggered automatically — depth is earned, not pushed.
• Web Signal Surfacing — if a new percept signal matches the active topic, surfaces it as a quiet inline link without interrupting flow.

Percept Inbox Daemon

Background daemon (vektor-percept.js) that watches ~/.vektor/inbox/ for dropped files and auto-processes them into MAGMA memory without any user action. Supported formats: .txt, .md, .json, .transcript, .log. Pipeline per file: detect type → extract text → LLM synthesis (title, summary, entities, decisions, actions, tags) → store structured note in MAGMA → move to done/. Failed files move to error/ with a processing receipt.

Commands: vektor percept — start daemon (blocks) · vektor percept --once — process inbox once then exit · vektor percept --dir <path> — watch custom directory · vektor percept --no-llm — heuristic only, no LLM cost · vektor percept status — show inbox stats.

Percept Worker CLI

Standalone thinking-loop CLI (percept.js) for interactive session-based memory work. Provider-agnostic: Groq, Ollama, OpenAI, Claude, Mistral, Together AI, OpenRouter, Cohere, xAI, DeepSeek, LM Studio, MiniMax, NVIDIA NIM, Perplexity. Configurable via ~/.vektor/config.json. Separate fast model for worker and distillation passes, session model for conversation. Briefings via /insights [days].

Bug Fix — Sovereign Screener Blocking Legitimate Writes

sovereign.js contained override in its RISK_TOKENS list. Any vektor_store call with content including that word silently returned { blocked: true } with no error raised and no write to the database. Removed override from RISK_TOKENS.

Bug Fix — sovereignRemember Dropped importance Options

The sovereignRemember wrapper accepted only a single argument (input), silently swallowing the { importance: imp } options object passed by the MCP bridge on every store call. All writes succeeded but landed with default importance regardless of the value specified. Fixed: sovereignRemember(input, opts = {}) now accepts and forwards opts to originalRemember. Affected module: sovereign.js.

Bug Fix — FTS5 Content Table Datatype Mismatch

memories_fts was configured with content_rowid=’id’ but memories.id is a TEXT column. SQLite’s actual integer rowid is the correct key. Under specific BM25 query patterns this produced a silent datatype mismatch error that broke recall. Fixed: FTS index rebuilt against the real integer rowid via migration script migrate-137.js. Post-fix result: memories and FTS counts aligned, BM25 test hits confirmed live. Affected module: slipstream-db.js.

Bug Fix — MCP Tool Schema Unhandled Parameters

anticipated_queries and supersedes_id were advertised in the MCP tool description but not handled by the store() function, causing schema validation noise on every store call. Parameters stripped from schema and handler support added. Affected module: memory.js.

Docs — Sidebar & Navigation

The integrations sidebar now lists all 21 entries with anchor links for direct navigation. The Downloads page "Works With" count and all integration tiles link directly to the corresponding guide section.

v1.5.4

Supersession Chains

Memory systems that accumulate contradictions degrade over time — both sides of a preference change sit in the database with equal weight, both get recalled, and the agent has no way to know which is current. Supersession chains fix this. When a new memory arrives that is semantically similar to an existing one, VEKTOR marks the old memory as superseded via a superseded_by forward pointer and timestamps the replacement. Active recall filters superseded memories out with WHERE superseded_by IS NULL. The full chain is preserved for provenance — you can walk backwards through what the agent believed at any point in time, but only current state is surfaced during normal operation. Implemented in vektor-dedup.js via a Proxy that intercepts every remember() call and runs a near-duplicate check before writing.

Query Prefixing

Structured context is now prepended to queries before vectorizing at recall time. Short or ambiguous inputs that previously produced noisy embedding results benefit most — the prefix anchors the vector in a more meaningful region of the embedding space, improving semantic retrieval accuracy without changing how memories are stored.

Parallel Detail Pass

After initial recall scoring, a secondary sweep fetches full memory content for the top-ranked candidates rather than relying on indexed summaries. The result is more accurate recall on complex or multi-part queries where summary-level representations lose important nuance. Adds a small latency cost on high-recall queries; threshold-controlled and off by default for lightweight sessions.

HyDE Recall Channel

Hypothetical Document Embeddings — the recall layer now generates a hypothetical answer to the incoming query and uses that as an additional recall vector alongside the original. Surfaces memories that are semantically related but share little surface vocabulary with the query. Particularly effective for preference and fact lookups where the stored memory was phrased differently from how the question was asked.

Critical FTS5 Stability Fix

Resolved a recurring no such module: fts5 crash that could occur on every new install or after a Node version change. Root cause: purgeBrokenFTS5() was called after the FTS5 availability probe inside applyBM25Schema() — if FTS5 was unavailable the function returned early, leaving stale triggers in place. Any subsequent vektor_store call would then crash with a module error. Fix: purgeBrokenFTS5(db) is now called unconditionally at the top of applyBM25Schema(), before the probe. Affected module: slipstream-db.js. No database migration required.

v1.5.2

JOT AI Toolbar

Seven one-click AI actions added to the JOT synthesis pane toolbar. Each action streams output directly into the synthesis panel, replacing live synthesis until typing resumes:

• Summarise — condenses notes to essential points
• Flashcards — converts content into Q&A flashcard pairs for review
• Whitepaper — expands notes into a structured long-form document
• Actions — extracts actionable tasks and next steps
• Tags — auto-generates relevant topic tags
• Titles — suggests document titles based on content
• Improve — rewrites for clarity, flow, and concision

Named Session Management

JOT sessions are now named and persistent. Save any session with a custom name; list, reopen, and delete sessions from the sessions panel. Sessions are stored in the local VEKTOR vault and survive restarts.

Arxiv Research Panel

When note content crosses a minimum-length threshold, JOT automatically queries the arxiv API and surfaces related academic papers below the synthesis pane. Results update with a 1-second debounce as notes evolve. Each result shows title, authors, date, and abstract excerpt with a direct link to arxiv.org.

Math Evaluator & Unit Converter

Collapsible utility panel embedded in JOT. Handles inline math expression evaluation (no submit button — results appear as you type) and unit conversion across length, weight, temperature, and currency. Currency pairs use live rates; all other conversions are fully offline.

Clickable Insight Expansion

Each synthesised insight bullet now renders with a clickable circle. Clicking expands that specific insight inline with a deeper elaboration streamed live from the model. Clicking again collapses it. Expansion does not interrupt the main synthesis stream.

v1.5.1

JOT — Split-Panel Note & Synthesis Interface

vektor jot — new GUI mode providing a split-panel interface for note-taking with live AI synthesis. Left pane accepts freeform notes; right pane streams a structured synthesis with a 600ms debounce on keystrokes. Synthesis is tiered by content length: short content gets quick insight bullets; medium content gets structured insights with connections; long content gets full thematic synthesis with tensions and recommendations.

The model used for synthesis is drawn from the active provider in your VEKTOR config and can be overridden per-session from the settings panel.

Streaming Token Render

Synthesis output streams token-by-token into the right pane using server-sent events. The UI renders tokens as they arrive — no waiting for full completion. A subtle cursor indicator shows when synthesis is in progress.

v1.5.0

New MCP Tools

vektor_status — lightweight health check returning memory count, active namespace, last store timestamp, top tags, and DB size in ~10 tokens. Call at session start for orientation without a full recall.

vektor_related — traverses all graph edges for a given memory ID. Returns Zettelkasten links (SUPPORTS, EXTENDS, CONTRASTS, RELATED, PREREQUISITE) and MAGMA co-occurrence edges with types and weights.

Auto-Briefing on First Recall

The first vektor_recall call each session now returns an inline session_briefing field — a compact digest of recent stores, open decisions, and top-priority items. No separate vektor_briefing call needed for orientation.

MAGMA Graph Exposure

The vk_graph_nodes and vk_graph_edges tables (co-occurrence, temporal, causal edges) are now fully queryable via vektor_related and vektor_graph. Edge weights and types surface in recall results for high-connectivity memories.

SSH Deployment Tools (CLOAK)

cloak_ssh_exec — run any shell command on a remote server. Auto-classified into read vs. destructive tiers; destructive commands require cloak_ssh_approve before execution.

cloak_ssh_plan — multi-step atomic deployment with auto-backup before each write step and one-step rollback on failure.

cloak_ssh_approve / cloak_ssh_rollback — safety gate and rollback for destructive SSH operations.

DXT Extension

New vektor-slipstream-dxt/ bundle: single-file Claude Desktop extension with embedded MCP server, manifest, and user config UI. Installs via drag-and-drop with no manual JSON editing.

v1.4.0 Major

Intelligence Modules

Axon — associative recall engine that traverses Zettelkasten link edges during search, surfacing related memories not directly matched by the query vector.

Cerebellum — procedural memory layer for multi-step skill sequences. Stores and retrieves agent workflows with step-level success/failure annotations.

Cortex — metacognitive monitor that tracks confidence trajectories across stored facts, flags contradictions, and suggests when to re-verify stale memories.

AUDN Log (audn-log.js) — append-only audit log recording every store, recall, and forget operation with timestamps, namespace, and caller identity.

Namespace Isolation

Full multi-namespace support in the MCP layer: all tools accept an optional namespace parameter. Memories stored in one namespace are invisible to recall in another unless global: true is passed explicitly.

Bulk namespace operations: rename, merge, export, and delete entire namespaces in a single call. Namespace stats included in vektor_status.

Boot Order & Patch System

boot-patch.js — deterministic boot sequence that applies pending migrations, warms the embedding model, and validates schema before the first tool call is served. Eliminates race conditions on cold start.

percept.js / percept-worker.js — background perceptual indexing worker that asynchronously re-embeds new memories without blocking the main MCP thread.

v1.3.7 Patch

Memory Management Tools

pin.js / forget.js — pin memories to prevent TTL expiry and selectively forget memories by ID, tag, or query match. Both exposed as MCP tools.

inspect.js — detailed memory inspector returning raw embedding vector (truncated), link edges, confidence score, and full metadata for any memory ID.

briefing.js — on-demand structured briefing engine returning recent, decisions, reminders, and conflict sections as structured JSON or formatted text.

export-import.js — cross-device memory portability: export to signed JSON bundle, import with automatic re-embedding and ID-collision resolution.

CLOAK Behaviour Patterns

Self-improving pattern store: behaviour profiles (mouse movement, scroll, keystroke timing) are scored win/loss after each stealth fetch. Patterns are promoted through Bronze → Silver → Gold tiers based on CAPTCHA pass rate.

cloak-recorder-auto.js — browser snippet that records real human interaction patterns and stores them in the pattern store for injection on future fetches.

New tools: cloak_pattern_list, cloak_pattern_stats, cloak_pattern_prune, cloak_pattern_seed, cloak_behaviour_stats.

TypeScript Types

Full types/index.d.ts covering all public API surfaces: store options, recall results, graph edges, namespace config, export bundles, and error types. Enables IDE completion for TypeScript and typed JavaScript projects.

v1.2.0 Major

Hybrid Recall Engine

BM25 keyword search (vektor-bm25-recall.js) runs in parallel with vector similarity search. Results are fused via Reciprocal Rank Fusion (RRF) into a single ranked list, improving recall for proper names, exact strings, and short queries.

New MCP tool vektor_recall_rrf: dual-channel recall exposed directly. Recommended over vektor_recall for code identifiers, people names, and product names where embeddings underperform.

Session Ingestion

vektor-session-ingest.js — end-of-session pipeline that feeds raw conversation text to an LLM and extracts discrete facts, decisions, and preference signals automatically.

Each extracted fact is stored with anticipated_queries — natural-language phrasings the user would use to search for it later, improving future recall quality without manual tagging.

New MCP tool vektor_ingest: accepts full conversation transcript, returns count of facts stored and IDs for review.

Confidence Scoring & Deduplication

vektor-confidence.js — importance-weighted confidence score on every stored memory, decaying gently over time and surfaced in recall results.

vektor-contradict.js — detects memories that directly contradict each other and flags them in recall results and briefings as unresolved conflicts.

vektor-dedup.js — cosine-similarity sweep marks near-duplicate memories and merges them on the next recall invocation.

Memory Versioning

vektor_store gains supersedes_id — pass the ID of an outdated memory to atomically mark it expired while storing the updated fact. Graph edges of type SUPERSEDES are created automatically, maintaining a full revision chain.

v1.1.0 Major

Namespace Isolation

vektor-namespace.js — each agent, project, or user session maintains a separate memory silo within one database. Namespace-aware recall scopes queries automatically; cross-namespace lookup is opt-in.

Knowledge Graph Server

vektor-graph-server.js and vektor-graph-ui.html — local HTTP server exposing the memory graph as an interactive force-directed visualisation. Nodes are memories; edges are Zettelkasten link types and MAGMA co-occurrence edges.

MCP tool vektor_graph: programmatic BFS/DFS traversal from a seed memory ID with configurable depth and edge-type filters.

Morning Briefing Scheduler

vektor-briefing-scheduler.js — configurable cron-style scheduler generating a briefing from recent memories and pushing it to a configurable endpoint or stdout.

MCP tool vektor_briefing: on-demand structured briefing with sections: recent, decisions, reminders, conflicts.

Sleep & Self-Organisation

vektor-sleep.js — offline consolidation: re-embeds low-confidence memories with updated model weights, prunes expired memories past TTL, rebuilds BM25 index. Runs during agent idle periods or via vektor sleep CLI.

vektor-selforg.js — LLM-driven background pass that assigns tags, importance weights, and Zettelkasten link suggestions to recent stores. Tags flow through to the vektor_status top_tags fingerprint.

v1.0.0

Persistent Memory Core

First public release — local-first persistent memory for AI agents.

vektor_store writes facts with importance, TTL, tags. vektor_recall returns top-K semantic results.

SQLite + sqlite-vec for native vector search. All data on-device.

MCP Server

Full MCP server — plugs into Claude Desktop, Roo Code, and any MCP-compatible client via DXT.

Initial tools: vektor_store, vektor_recall, vektor_delta, tokens_saved.

CLI and TUI

vektor.mjs — full CLI built with Ink (React terminal UI). Commands: setup, doctor, recall, store, export, import.

Interactive REPL for memory inspection. Doctor validates DB integrity, embedding model, and MCP config.

Export and Migration

Full database export to portable JSON — memories, embeddings, tags, metadata. Schema migration runner with version tracking; in-place upgrades without data loss.

Licence and Security

Compiled licence enforcement via ByteNode — tamper-resistant, validated at startup. No telemetry. No cloud API calls for core operations.