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Workspace memory: personal and organization memory for AI clients

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Una pull request collegata è già stata integrata.

  • #1152 di @helpcodeai — integrata

Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
25/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
github, postgresql, sql, typescript
Ambito
ai-infra-agents, authentication, backend, database

Direzione di ricerca

Read the follow-up issues #1145 and #1148, then inspect ee/licensing, the /mcp/:serverId tool registration, organization_members, and the Settings > Users and Memory areas. The proposal specifies scopes, access levels, approval flow, secret detection, and PostgreSQL full-text storage, but does not identify existing implementation files or tests. Done means delivering the licensed workspace memory feature across storage, MCP tools, access controls, and UI.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Follow-up to #1145 and #1148. Skills tell an AI client how a company works. What is missing is what it has learned: facts ("STAMMKUNDE means a customer with a framework agreement"), preferences of a person ("answer in Italian, numbers as tables") and notes an assistant should find again next week, in any client, for the same user or for the whole team.

Proposal

Workspace memory, available with an Enterprise licence (Cloud and self-hosted), gated like single sign-on: the code is in core, the licence check lives in ee/licensing.

Scopes

  • Personal: one member. Only that member can read it, admins included; admins can erase it (data protection) but not read it.
  • Organization: the company memory.
  • (Team scope via roles comes later.)

Kinds: fact, preference, note. Memory is served as data, never as instructions; skills stay the only instruction-grade content.

MCP tools (only on /mcp/:serverId; the shared /mcp toolset is unchanged), registered per member level:

  • memory_search(query, scope?): full-text search over the caller's personal memory and the active organization memory.
  • memory_save(content, kind, scope, tags?): personal directly; organization as a proposal or directly, depending on the workspace switch.
  • memory_forget(id): the caller's own personal items only.

Per-member access (organization_members.memory_access): inherit (workspace default) | none | read | personal | contribute. Default for the workspace is personal. Set one by one or in bulk under Settings > Users.

Workspace switch for organization writes from AI clients: approval (default, an admin or editor approves under Memory) or auto. Provenance (who, which server and client) is kept either way.

Safety: content that looks like a secret (API keys, tokens, passwords, private keys) is refused; size limits per item and per workspace; no cross-workspace access.

UI: a Memory page with "My memory", "Company memory" and "Pending" tabs, plus the workspace settings; a Memory column on Settings > Users.

Storage

New table memory_items (organization, scope, owner, kind, content, tags, status, source, author, approver, timestamps) with a Postgres full-text tsvector (simple configuration, multilingual) and a GIN index; new column organization_members.memory_access. No new dependency. Embeddings can come later as an option.

Lingua principale
TypeScript
Stelle
856
Fork
82
Merge medio
7h 39m
PR unite (30g)
227

Preparare l'ambiente

Questo progetto non fornisce container di sviluppo, Dockerfile né guida per i contributori, quindi l'ambiente è a tuo carico: parti dal suo README e consulta la nostra guida al primo contributo per i passaggi generali.

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

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