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Show HN: Llmem – Local persistent memory for AI coding, no embeddings

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Show HN: Llmem – Local persistent memory for AI coding, no embeddings
TL;DR · WeSearch summary

llmem Local-first persistent memory for AI coding agents. Give Claude Code, Cursor, and other MCP clients a memory that survives across sessions — stored in a single SQLite file, retrieved with BM25, with no embeddings, no vector database, and no external API calls. Built for Claude Code, Cursor and other local agents via MCP (Model Context Protocol).

Key facts
About this source

Hacker News (AI / LLM) files mainly under ai. We currently carry 3,940 of its stories.

Original article
GitHub
Read full at GitHub →

Story provenance

Source · retrieval · rights · ranking — open for full record
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Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.

Record

Original publisherGitHub
Canonical URLhttps://github.com/netrixone/llmem
Publication timeFri, 07 Aug 2026 08:40:08 +0000
Retrieval time2026-08-07T08:50:41.544Z
Last seen2026-08-07T08:50:41.544Z
Headline sourcePublisher (no WeSearch rewrite)
Excerpt sourcepublisher body
Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
SummaryWeSearch · cerebras-chat (WeSearch summarizer)
Summary source textcontentText
Citation coverageSummary is a WeSearch-generated derivative; primary citation is the original publisher URL.
ClusterHxipwB3Tmrwz · 1 stories
Cluster logicGrouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison.
Ranking reasonStory pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking.
Publisher visitYes — open original
Substitutes article?No — link-out required for full text

Rights status (four layers)

Publisher-declared
No publisher-confirmed rights record for this source yet.
Machine-readable
No source-specific machine-readable restriction detected beyond the public feed.
WeSearch interpretation
WeSearch declared handling (basis: Derived from the published RSS/Atom feed). This is WeSearch policy, not a legal grant on the publisher's behalf.
Unknown
Retrieval and training permissions are not asserted unless the publisher confirms them.

WeSearch handling by dimension

Indexing May the item be indexed (stored, ranked, made findable)? Allowed
Snippet May a short excerpt of the publisher's text be shown? Allowed
AI summary May WeSearch generate its own short summary of the article? Limited
Retrieval / RAG May the content be exposed for third-party retrieval-augmented generation? Not asserted
Model training May the content be used to train AI models? Not asserted
Commercial reuse May the content be reused commercially? Not permitted

Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

llmem Local-first persistent memory for AI coding agents. Give Claude Code, Cursor, and other MCP clients a memory that survives across sessions — stored in a single SQLite file, retrieved with BM25, with no embeddings, no vector database, and no external API calls. Built for Claude Code, Cursor and other local agents via MCP (Model Context Protocol). Why llmem Local-first — Everything runs on your machine: one SQLite file (~/.llmem/data.db), no network dependencies, no per-query cost. No embeddings, no vector DB — Retrieval is BM25 lexical search with optional WordNet synonym expansion. The tradeoff is deliberate: weaker on heavy paraphrase than an embedding model, but zero external services to run and zero cost per query.

Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.

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