Memory MCP
A knowledge-graph-based memory system for AI agents that enables persistent information storage between conversations.
README
Memory MCP
A knowledge-graph-based memory system for AI agents that enables persistent information storage between conversations.
Features
- Persistent memory storage using a knowledge graph structure
- Entity-relation model for organizing information
- Tools for adding, searching, and retrieving memories
Tools
The system provides the following MCP tools:
load_knowledge_graph(): Retrieves the entire knowledge graphadd_entities(entities): Adds new entities to the memoryadd_relations(relations): Creates relationships between entitiesadd_observations(entity_name, observations): Adds observations to existing entitiesdelete_entities(entity_names): Removes entities from memorydelete_relations(relations): Removes relationshipssearch_nodes(query): Searches for entities and relations matching a queryopen_nodes(names): Retrieves specific entities and their relationships
Usage
Run the agent with:
uv run memory_agent.py
The agent will automatically:
- Load its memory at the start of conversations
- Reference relevant information during interactions
- Update its memory with new information when the conversation ends
Exit a conversation by typing q.
Configuration
Set the memory storage location with the MEMORY_FILE_PATH environment variable (defaults to memory.json).
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