Show HN: Memanto.ai
Memanto is a free, open-source companion agent designed to manage long-term memory for various AI coding assistants. It operates locally on user machines to ensure data privacy and eliminate API costs while supporting over twenty different AI agents. The tool utilizes a semantic backend and Markdown files to provide instant context retrieval without requiring external vector databases.
- ▪Memanto is an open-source tool that runs locally on user machines to manage long-term memory for AI agents.
- ▪It supports integration with over twenty agents, including Claude Code, Cursor, and Codex, out of the box.
- ▪The system allows for full data ownership by converting between a semantic backend and human-readable Markdown files.
- ▪Memanto claims to achieve sub-90ms recall times and zero LLM token costs for the write path.
- ▪Installation requires only a single pip command, eliminating the need for separate vector databases or backend services.
Hacker News (AI / LLM) files mainly under ai. We currently carry 6,022 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
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 publisher | MEMANTO by Moorcheh |
| Canonical URL | https://memanto.ai/ |
| Publication time | Tue, 22 Sep 2026 15:02:57 +0000 |
| Retrieval time | 2026-09-22T15:13:50.990Z |
| Last seen | 2026-09-22T15:13:50.990Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | None |
| Cluster logic | Not yet clustered, or no peer story found in the clustering window. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
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
100% FREE · OPEN SOURCE · RUNS ON YOUR MACHINEMemory that AI Agents Love!Memanto is a companion agent dedicated to managing long-term memory for all your AI agents. It curates key insights, consolidates context across sessions, and briefs your agents the moment they start—so context is never lost.Get Started on GitHubWhy Memanto?MUniversal Agent SupportWorks automatically out-of-the-box with AntigravityClaude Code, CursorCursor, CodexCodex, and 20+ other agents..mdvecNo Lock-InFully convertible between a fast semantic backend and human-readable Markdown (.md files in an LLM Wiki format).
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Excerpt limited to ~120 words for fair-use compliance. The full article is at MEMANTO by Moorcheh.
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