LoreConvo: MCP Server Adds Persistent Session Memory to Claude Code

What LoreConvo Does
LoreConvo is a local-first MCP server that gives Claude persistent session memory, solving the problem of context loss between sessions. The developer built it while working on a complex finance automation project with a 19-node LangGraph pipeline and multiple MCP servers.
Key Features
- Auto-saves sessions via Claude Code hooks (post-session hook triggers save)
- Auto-loads relevant context on session start (pre-session hook calls get_recent_sessions)
- Cross-surface persistence — context carries between Claude Code, Cowork, and Chat
- Full-text search across all past sessions
- 12 MCP tools for AI-native access
- Local-first architecture using SQLite
Practical Impact
Sessions that used to start with 5 minutes of re-contexting now start with Claude already knowing the project state, recent decisions, and open questions. This saves roughly 3,000-8,000 tokens per session in re-contexting overhead.
Companion Tool
The developer also built LoreDocs for project knowledge management, featuring 34 MCP tools, multi-vault architecture, document versioning, and context injection.
Availability
Both tools are free for personal use under BSL 1.1 (converts to Apache 2.0 in 2030). The code is available on GitHub: LoreConvo at https://github.com/labyrinth-analytics/loreconvo and LoreDocs at https://github.com/labyrinth-analytics/loredocs.
📖 Read the full source: r/ClaudeAI
👀 See Also

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Anamnese: A Personal Memory System for Claude via MCP
Anamnese is a free tool that stores personal context—facts, projects, goals, tasks—and connects to Claude via MCP, allowing the AI to access this information at the start of every conversation.

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Aura Research: Local tool compiles documents into AI-navigable wiki with persistent memory
Aura Research is an open-source tool that processes raw documents (PDFs, papers, notes, code, 60+ formats) into a structured markdown wiki with backlinked articles, concept pages, and a master index. It compresses everything into a .aura archive optimized for RAG retrieval and runs 100% locally with no data leaving your machine.