Thanks for the contribution. The core gap is real — the MCP server has no delete path, and delete_thought fills it cleanly: a pre-flight existence check (so the caller gets a clear not-found), a confirmation response, and a standalone connector. The README is honest that this is a hard delete.

One design question worth a maintainer decision: this exposes a hard delete to an AI client, with recovery only via Supabase backups and audit left optional (the README points to schemas/thought-audit / #230 as an opt-in extension). An LLM calling delete_thought on a wrong or hallucinated UUID is unrecoverable. Worth deciding whether OB1's delete path should be hard delete (this PR) or default to a recoverable soft delete with built-in audit. The code itself is correct for the hard-delete design it implements.

Needs product decision on the delete-path design; recommend maintainer review.

— Alan (community reviewer; non-binding)

@alanshurafa Alan's question is load-bearing — you're right that exposing a hard delete to an AI client with backup-only recovery is a design decision, not just a process concern. Having thought about it more, I think the better default for OB1's delete path is a recoverable soft-delete with built-in age-out.

Preferred design: add a deleted_at TIMESTAMPTZ column to thoughts. The delete_thought tool sets deleted_at = NOW() rather than issuing a DELETE FROM. All read queries — search_thoughts, list_thoughts, capture_thought responses, stats — filter WHERE deleted_at IS NULL, so normal callers see no change in semantics. A scheduled age-out job (Supabase cron or an external timer) hard-deletes rows where deleted_at < NOW() - INTERVAL '30 days' — open to a different retention window if there's prior art in the repo. A new recover_thought(id) RPC sets deleted_at = NULL for any row still within the window.

The practical gain: an LLM calling delete_thought on a wrong or hallucinated UUID is recoverable for 30 days without needing to touch Supabase backups or an optional audit schema. The cost is real — this is bigger than a single connector change. It requires a new migration, touches every read query in the core server, and needs the age-out job placed somewhere. Not a trivial scope expansion.

Two paths for sequencing: (a) revise this PR in-place to implement soft-delete + age-out + recovery — bigger commit but a cleaner story for the delete path; or (b) merge or leave this PR as-is and open a follow-up PR that adds soft-delete as a first-class schema feature, superseding or wrapping this connector. Nate, which sequencing makes more sense from a release cadence standpoint?

Thanks again, Alan — this was the kind of question that actually changed the design.

Any update on this please? I would love to be able to delete thoughts no longer relevant, but I do not need to go the full dashboard app route

Hi Jodie — thanks for jumping in. Genuinely useful to hear from someone who wants the capability but doesn't want to stand up a whole dashboard for it.

Quick status: the function in this PR works. What's pending is the maintainer-side call on sequencing — revise in place, or merge and follow up with the soft-delete refinement. I sketched the soft-delete design in the 2026-05-21 comment further up, so I won't re-litigate. How I got there is worth a few lines, though, because it touches your use case.

Earlier in 2026 I imported about 1,939 thoughts from Fastmail via IMAP. The April audit found roughly 17% were straight noise — marketing, transactional, automated. Unglamorous lesson: bytes you might want tomorrow shouldn't disappear today. Then Alan flagged the LLM angle on 2026-05-20 — an AI calling delete on a hallucinated UUID is unrecoverable, a worse failure mode than a missed cleanup. Soft-delete with a 30-day window covers both, and a human checkpoint already exists in the rhythm: Pinky (the curation agent — and yes, she curates the Brain; NARF, I didn't pick the names so much as fail to resist them) re-embeds null vectors and spot-checks weekly, then runs a monthly full re-slice — ledger regenerated, distribution deltas surfaced, links built at 0.85–0.95 cosine, merges at 0.95 and above. The 30-day age-out is one full maintenance cycle, not an arbitrary number. The April sprint itself — 3,146 thoughts in 30 batches, 69% pass / 22% reclassify / 17% dup-candidate / 1% low-value — produced zero auto-deletions. Everything destructive routes back through me.

The part I keep wondering about, and I want to flag as speculation rather than a roadmap claim: what we're sketching looks a little like how brains use sleep. Monthly consolidation is already the engineering version — dedup, abstraction, link-building during idle time. The more speculative version is whether the brain should also dream — synthesize patterns across captured traces, surface emergent abstractions, and let truly low-signal traces fade as part of the rhythm rather than as a separate delete event. I don't know if "dreaming" is the right metaphor or whether it leads anywhere useful, but it feels like a question worth opening: should a memory system that's already consolidating do something more reverie-like during idle time, and would that reframe how we think about deletion at all? Curious where the room lands.

Short version for you, Jodie: the capability is real and works today. The hard-vs-soft call is what's holding the merge, and that one isn't mine to make. Nothing you need to do — but if any of this lands, I'd love your read.