mcp-memory-py

# Knowledge Graph Memory Server A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats. This is a Python port of the [original](https://github.com/modelcontextprotocol/servers/tree/main/src/memory) reference server (version 0.6.3). I took the opportunity to do some refactoring of the code, mostly aided by Cline (and Claude Sonnet 3.5). ## Core Concepts ### Entities Entities are the primary nodes in the knowledge graph. Each entity has: - A unique name (identifier) - An entity type (e.g., "person", "organization", "event") - A list of observations Example: ```json { "name": "John_Smith", "entityType": "person", "observations": ["Speaks fluent Spanish"] } ``` ### Relations Relations define directed connections between entities. They are always stored in active voice and describe how entities interact or relate to each other. Example: ```json { "from": "John_Smith", "to": "Anthropic", "relationType": "works_at" } ``` ### Observations Observations are discrete pieces of information about an entity. They are: - Stored as strings - Attached to specific entities - Can be added or removed independently - Should be atomic (one fact per observation) Example: ```json { "entityName": "John_Smith", "observations": [ "Speaks fluent Spanish", "Graduated in 2019", "Prefers morning meetings" ] } ``` ## API ### Tools - **create_entities** - Create multiple new entities in the knowledge graph - Input: `entities` (array of objects) - Each object contains: - `name` (string): Entity identifier - `entityType` (string): Type classification - `observations` (string[]): Associated observations - Ignores entities with existing names - **create_relations** - Create multiple new relations between entities - Input: `relations` (array of objects) - Each object contains: - `from` (string): Source entity name - `to` (string):…