
local-memory-mcp
Updated 2d agoby vheins
@vheins/local-memory-mcp
MCP Local Memory Service is a high-performance Model Context Protocol (MCP) server that provides long-term, high-signal memory for AI Agents (such as Claude Desktop, Cursor, or Windsurf).
Built with a Local-First philosophy, this service stores architectural decisions, code patterns, and critical facts locally on your machine using SQLite and AI-powered Semantic Search.
🚀 Key Features
- 🧠 Semantic Search (V2): Find memories based on meaning, not just keywords, using the
all-MiniLM-L6-v2model locally with hybrid TF-IDF + vector ranking. - 🔄 Tech-Stack Affinity: Share knowledge across repositories intelligently based on technology tags.
- 🛡️ Anti-Hallucination Guard: Strict similarity thresholds and decision conflict detection.
- 🧩 Knowledge Graph: Structured entities, relations, and observations with auto-extraction via offline NLP.
- 🕰️ Time Tunnel: Query memories with natural language dates ("yesterday", "last week").
- 📉 Soul Maintenance: Biological-style memory decay with tag immunization — automatically archives obsolete memories.
- 🤖 Agentic Tools: Agent-context recall, structured decision logging, session summarization.
- 📊 Glassy Dashboard: Visualize memories, tasks, handoffs, knowledge graph, and interaction logs through a modern Svelte 5 interface.
- 🔍 Codebase Index: Index and query source code structure — search for functions, classes, interfaces, types, and enums across your projects. Uses tree-sitter WASM for fast parsing with incremental updates.
- 🧭 Codebase Search & Trace: Search indexed symbols with ranked results (
search_symbols), inspect file-level declarations (get_file_symbols), explore architecture overviews (get_architecture), and trace symbol definitions across your codebase (trace_symbol).
Drop-In Upstream Compatibility
Compatible with Beledarian/mcp-local-memory clients: remember_fact, remember_facts, recall, forget are built-in aliases.
🔌 MCP Usage & Configuration
Add this service to your AI Agent (Claude Desktop, Cursor, Windsurf, etc.) using one of the methods below.
💡 Recommendation: If your MCP runs frequently (agents, CI, automation), avoid
npxand use a global or local install instead. It reduces unnecessary NPM downloads and speeds up Agent startup.
🚀 Quick Start (Zero Setup)
Best for first-time users or quick testing. This uses npx to run the server without any permanent setup.
"local-memory": {
"command": "npx",
"args": ["-y", "@vheins/local-memory-mcp"],
"type": "stdio"
}
- Uses
npx: Automatically handles the execution. - Tradeoff: May re-download the package in some environments and is not optimal for frequent execution.
⚡ Recommended for Production / Frequent Usage
This method ensures the fastest startup times and maximum reliability for daily use.
-
Install globally:
npm install -g @vheins/local-memory-mcp -
Add to your configuration:
"local-memory": { "command": "local-memory-mcp", "type": "stdio" }
- Faster startup: No network checks required on every start.
- No repeated downloads: Saves bandwidth and avoids NPM registry dependency.
- Better for automation: More stable for heavy-duty Agent workflows.
🧠 How It Works (Important Insight)
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