@modelcontextprotocol/server-memory
Anthropic's official reference MCP server for persistent agent memory using a local knowledge graph. Agents can create entities, relations, and observations that persist across sessions.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
No external network calls. All data stays local. No credentials needed. Appropriate for local development; for production use a proper secrets manager for sensitive memories.
⚡ Reliability
Best When
Your agent needs to remember things between sessions. The canonical reference implementation for agent memory — zero config, persists to local JSON file.
Avoid When
You need semantic similarity search over memories (use Chroma or Qdrant instead), or you're running multiple parallel agents that need shared memory.
Use Cases
- • Storing user preferences and facts that an agent should remember across conversations
- • Building a knowledge graph of entities and their relationships for reasoning
- • Maintaining agent state between sessions without requiring external databases
- • Tracking project context, decisions, and observations across long-running tasks
- • Personal assistant memory — remember names, preferences, past interactions
Not For
- • High-volume data storage (designed for knowledge graph, not document store)
- • Shared memory across multiple agent instances (local file — not distributed)
- • Semantic/vector search (exact entity/relation lookup only, no embedding search)
Interface
Authentication
No authentication. Data stored in local JSON file (memory.json) on disk. File path configurable via MEMORY_FILE_PATH environment variable.
Pricing
MIT licensed, free. Requires Node.js runtime.
Agent Metadata
Known Gotchas
- ⚠ Knowledge graph stored in single JSON file — concurrent access from multiple sessions can cause corruption
- ⚠ No deduplication for observations — agent calling add_observations twice with same text creates duplicates
- ⚠ search_nodes is exact/fuzzy text match, not semantic — 'user likes dogs' won't match 'user prefers canines'
- ⚠ Entity types are free-form strings — no schema enforcement, easy to create inconsistent ontologies
- ⚠ File can grow large with heavy use — no built-in pruning or archival
Alternatives
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Scores are editorial opinions as of 2026-03-07.