Memory Engine MCP server

<!-- mcp-name: io.github.simoneb79/memory-engine-mcp -->

🧠 Memory Engine MCP

Local-first, graph-aware long-term memory for AI assistants. SQLite + semantic search + knowledge graph + MCP tools for agents that need continuity.

Works with Claude Desktop · Claude Code · Cursor · Cline · Windsurf · OpenClaw · any MCP client

Why Memory Engine?

Most MCP memory servers are either simple key-value stores or plain text search wrappers.

Memory Engine is different: it models memory as typed atoms connected by typed bonds, then retrieves context with a hybrid ranking pipeline that combines:

• full-text search (SQLite FTS5)
• semantic similarity via local Ollama embeddings
• confidence, recency, and weight
• graph expansion from related memories

The goal is not just storage. The goal is a memory system that can recall, connect, decay, curate, and learn over time.

Highlights

• Local-first — SQLite database, optional local embeddings via Ollama, no required cloud API.
• MCP-native — exposes 35 tools through FastMCP.
• Graph-aware recall — expands top hits through bidirectional bonds for richer context.
• Semantic search — meaning-based retrieval with nomic-embed-text.
• Markdown coexistence — import existing notes one-way without replacing your human-readable memory.
• Error memory — remembers mistakes and corrections, with auto-promotion to preferences after repeated failures.
• Cognitive curator — non-destructive maintenance pass for compaction, bond suggestions, duplicate detection, and isolated atom classification.
• Session watcher — canonical OpenClaw SQLite ingestion (schema 17), reset-aware digests, and JSONL legacy fallback.
• Backup & restore — full SQLite snapshots, JSON export/import, verified restores with automatic safety backups.
• Auth & hardening — optional API token, secure bind, input validation, rate limiting.
• Test suite — 144 tests covering CRUD, ranking, migrations, auth, backup, concurrency, and transcript ingestion.
• Benchmark — CLI recall quality suite with Precision@K, MRR, latency percentiles.

Architecture

AI assistant / MCP client
        │
        ▼
FastMCP server — 35 tools
        │
        ▼
Memory engine — hybrid ranking, graph recall, decay, learning
        │
        ├── SQLite — atoms, bonds, FTS5, JSON metadata, versions
        ├── Ollama — optional local embeddings
        ├── Curator — conservative maintenance
        └── Session watcher — OpenClaw SQLite + JSONL fallback

MCP Tools

Memory

Knowledge graph

Shortened. The full README is on GitHub.