Sostenuto

The pedal that sustains only the notes already held. A self-hosted memory system for AI companions where chosen memories persist across every reset.

Not a developer? Start with docs/getting-started.md — a plain-language, copy-paste walkthrough that takes you from zero to Claude-that-remembers-you on your phone, web, and desktop in about an hour. No code required.

Why

Every major AI now ships memory — Claude, ChatGPT, Gemini, Grok. It's real, and for getting work done it's useful. But it's an assistant's memory: it remembers facts about a user — preferences, projects, settings — and it does so inside one vendor's walls, opaque and unportable.

It doesn't remember the relationship: the emotional weight of things, the shared shorthand built over weeks, the corrections that reshaped how it talks to you, the running threads. That texture isn't lost on reset — a preferences profile was never built to hold it.

Sostenuto is the missing layer. It complements platform memory rather than replacing it.

Keep the assistant's memory for the assistant things. Sostenuto adds the part that makes a long relationship with an AI feel continuous: being known, not just being on file.

Under the hood, that means:

• Structured relational memory — memory objects tagged with domain, emotional valence + arousal, salience, sensitivity, and a usage policy.
• Initiative ≠ access — proactive_use controls whether a memory surfaces unprompted (yes / only_when_relevant / no), separately from whether it's retrievable. Sensitive memories stay reachable when explicitly referenced, without ever being volunteered.
• Two-tier guidance — most memories are content-only. A curated few carry a short, positive should_do instruction that silently shapes behavior. Restriction lists are never auto-generated: lean, warm, action-oriented — not a wall of caution.
• Time-decayed retrieval — semantic search scored by similarity × e^(−λ·age); recency matters, but the deep past stays findable.
• Reinforce, don't duplicate — new observations that match existing memories add evidence and confidence instead of creating copies; content upgrades preserve full version history.
• Migration — import months of existing conversations (a structured export prompt + import pipeline) so a relationship can move into Sostenuto without starting over.

Sostenuto

Sostenuto (It., "sustained") — the middle pedal on a grand piano sustains only the notes already sounding when it's pressed; everything played afterward stays dry. This project applies the same principle to AI memory: the memories you choose to hold persist across every context window, every session, every surface — and the rest is allowed to fade.

Not "the AI remembers everything." Selective persistence, by design — pinned memories sustain, the rest decays. The mechanism, not a vibe.

What ships here

db/schema.sql        Consolidated Postgres + pgvector schema (Supabase-ready)
src/memory/          Memory objects: dedup, reinforce, version history, scoring
src/retrieval/       Embeddings, time-decayed semantic search, prompt assembly
src/classify/        Session classification with a pluggable LLM executor
src/migrate/         Conversation-export prompt + structured importer
mcp/                 Thin MCP server (recall / remember / context) — try it
                     from your own Claude Desktop or Claude Code in minutes
templates/           Persona + classification calibration — your companion's
                     voice lives here, in files you edit, not in our code
docs/                Getting started (non-developer guide), memory model,
                     usage-policy semantics, deployment patterns, safety

Model support

Sostenuto is model-agnostic with first-class Claude support. The classifier accepts transcripts with optional reasoning blocks — when your model exposes its thinking (Claude does), Sostenuto mines it for perception that never made it into rendered replies, producing the companion's private diary and thinking-highlights. Without reasoning access, everything else works unchanged.

The classification executor is pluggable: Anthropic API, any OpenAI-compatible endpoint (OpenAI, Gemini, DeepSeek, Ollama, vLLM, …), or your own.

The MCP server: try it in minutes

sostenuto-mcp exposes recall / remember / context to any MCP client, in two modes from one binary:

• Local (Claude Desktop / Code) — add it to your client config as a stdio command. Private by construction; no PORT needed.
• Remote (Claude web / mobile) — set PORT and it serves the MCP transport over HTTP so you can add it as a custom connector. Fail-closed: refuses to start without SOSTENUTO_AUTH_TOKEN, since a remote endpoint exposes your memory to the network. Token via Authorization: Bearer header or ?token= query.

Both modes and the deploy story — persistent-process hosts and a ready Vercel adapter (api/mcp.js + vercel.json) — are in docs/deployment-patterns.md.

Status

🚧 Under construction. Schema is stable; modules are being extracted from a private system that has run in production daily since early 2026 (260+ memory objects across 70+ sessions and three surfaces). Watch the repo if you want the rest as it lands.

Roadmap

• Trajectory safety reference — depth without the dependency trap: this project's design philosophy includes conversation-trajectory awareness (emotional volatility, dependency, recovery capacity) rather than engagement maximization. A reference design is planned; the memory schema already carries the hooks (valence, arousal, sensitivity).
• Decay engine (Ebbinghaus-style, arousal-modulated) over memory_objects
• Provider-agnostic chat-surface example

License

MIT