rekal vs sparql-llm
rekal: rekal provides long-term memory for LLMs via an MCP server. It stores memories in a local SQLite file and retrieves them using hybrid search (BM25 keywords + vector semantics + recency decay). It works with any MCP-capable agent like Claude Code, Codex CLI, and OpenCode.; sparql-llm: SPARQL-LLM provides tools to empower Large Language Models (LLMs) to generate accurate SPARQL queries for specific endpoints. It integrates Retrieval-Augmented Generation (RAG) and SPARQL query validation against endpoint schemas to ensure relevant and precise query generation on large-scale knowledge graphs.
TL;DR
Persistent memory for coding agents across sessions to remember user preferences and decisions
Build LLM-powered chat services for knowledge graphs.
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