I built a deterministic memory layer for multi-client Claude Code setups

I’ve been building our agency operating system inside Claude Code, and memory quickly became one of the harder architectural problems.

Most AI memory systems use a global store with similarity-based retrieval. That can work for a single project, but it becomes risky when the same system handles multiple clients.

Relevant context for one client should never be retrieved while working on another.

So I built Agency Memory Kit around a different model:

Each client folder is its own source of truth.

The core mechanics are intentionally simple:

Context loads in a fixed, task-specific order instead of relying on fuzzy retrieval.

New learnings are written back to the relevant client folder.
Ambiguous learnings go into quarantine instead of being assigned automatically.
A weekly process deduplicates memory, recovers useful learnings from missed sessions, and extracts cross-client patterns without carrying over client-specific details.
Recurring tool mistakes can become proposed guardrails, but promotion, archiving, and hard blocks always require human approval.

The plugin is the engine. Your data stays in plain Markdown files inside your own folder structure, where it can be reviewed, edited, and versioned with Git.

The daily hooks run locally and send no telemetry. The optional weekly consolidation uses your own Anthropic API key.

Agency Memory Kit is currently on v0.2.10. It’s open beta, MIT licensed, and tested end to end on macOS and Windows.

If you’re building a multi-client or multi-project Claude Code setup, try it! I'm interested in what you would change.

Repo here:

https://github.com/krsnczky/agency-memory-kit

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I built a deterministic memory layer for multi-client Claude Code setups