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Rekal

Long-term memory for LLMs in a single SQLite file

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I got tired of repeating myself to my LLM every session. rekal is an MCP server that stores memories in SQLite and retrieves them with hybrid search (BM25 + vectors + recency decay). One file, local embeddings, no API keys.

HN · launched Apr 12, 2026 · 9 upvotes (top 45%) · 1 view

Niche: ai agent memory infrastructure · 350 launches, 11 in the last 7 days ▼ -58% · Explore this niche →

Category and tags

  • Horizontal
  • Data infrastructure
  • Developer
  • AI-native
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

Yes Rekal is an MCP server written on top of SQLite, sqlite-vec / FTS5 for hybrid BM25 and vector search, and an embedded local model (e.g. fastembed/onnx). This is a well-scoped weekend developer tool that an AI assistant can easily generate.

Discussion

10 comments analyzed.

Concerns raised: Python 3.14 requirement may limit adoption, Effectiveness unclear - requires significant intervention to keep agents using guardrails, Fixed weights (0.4/0.4/0.2) may not suit different use cases

Feature requests: Make hybrid search weights configurable, Add config file support (pyproject.toml or .rekal/config.yml), Different decay rates for different memory types

Competitors

Other products that read as similar to this one : 63 launches clear the similarity bar, closest 8 shown.

Attention rank: #30 of 64 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 136 days after the earliest competitor.

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