optimized-memory-mcp-server
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The optimized-memory-mcp-server is a Python-based fork of a Memory MCP Server, utilizing SQLite for backend storage, designed to demonstrate AI workflows and prompt design.
The optimized-memory-mcp-server is a knowledge graph memory server that provides a persistent memory implementation using a local knowledge graph. It allows for the storage and retrieval of information about users across different chat sessions. The server is designed to handle entities, relations, and observations, enabling the creation of a structured memory system. Entities are the primary nodes, each with a unique identifier, type, and list of observations. Relations define connections between entities, while observations are discrete pieces of information attached to entities. The server offers a comprehensive API for creating, managing, and querying the knowledge graph, making it a versatile tool for applications requiring memory persistence.
Features
- Entity Management: Create, delete, and manage entities with associated observations.
- Relation Handling: Define and manage directed relations between entities.
- Observation Management: Add and remove observations for entities.
- Graph Querying: Search and retrieve nodes and their relations based on queries.
- Comprehensive API: Provides tools for full graph management and querying.
Tools
create_entities
Create multiple new entities
create_relations
Create relationships between entities
add_observations
Add observations to entities
delete_entities
Delete entities and their relationships
delete_observations
Observation of deleting entities
delete_relations
Delete relationships between entities
read_graph
Read the entire knowledge graph
search_nodes
Search nodes based on query
open_nodes
Retrieve specific nodes by name
