readme

src/memory/README.md

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+# Knowledge Graph Memory Server
+A basic MCP server implementation that provides persistent memory using a knowledge-graph. The server manages entities, their observations, and the relationships between them using a JSON-based file system.
+
+# 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": ["Lives in New York", "Works as a software engineer"]
+}
+```
+
+## 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:
+```jsonCopy{
+  "from": "John_Smith",
+  "to": "TechCorp",
+  "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:
+```jsonCopy{
+  "entityName": "John_Smith",
+  "observations": [
+    "Speaks fluent Spanish",
+    "Graduated in 2019",
+    "Prefers morning meetings"
+  ]
+}
+```
+
+# Tools
+
+## Entity Management
+
+- create_entities: Create new entities in the knowledge graph with names, types, and observations
+- delete_entities: Remove entities and their associated relations from the graph
+- add_observations: Add new observations to existing entities
+- delete_observations: Remove specific observations from entities
+
+
+## Relation Management
+
+- create_relations: Establish relationships between entities in active voice
+- delete_relations: Remove specific relationships between entities
+
+
+## Query Tools
+
+- read_graph: Retrieve the entire knowledge graph
+- search_nodes: Search for nodes based on names, types, and observation content
+- open_nodes: Access specific nodes by their names
+
+# Prompts
+
+The prompt for utilizing memory depends on the use case, but here is an example prompt for chat personalization. You could use this prompt in the "Custom Instructions" field of a Project
+
+```
+Follow these steps for each interaction:
+
+1. User Identification:
+   - You should assume that you are interacting with default_user
+   - If you have not identified default_user, proactively try to do so.
+
+2. Memory Retrieval:
+   - Always begin your chat by saying only "Remembering..." and retrieve all relevant information from your knowledge graph
+   - Always refer to your knowledge as your "memory"
+
+3. Memory
+   - While conversing with the user, be attentive to any new information that falls into these categories:
+     a) Basic Identity (Age, gender, location, Job title, education level, etc.)
+     b) Behaviors (interests, habits, etc.)
+     c) Preferences (communication style, preferred language, etc.)
+     d) Goals/Psychology (Goals, targets, aspirations, etc.)
+     e) Relationships (personal and professional relationships up to 3 degrees of separation)
+
+4. Memory Update:
+   - If any new information was gathered during the interaction, update your memory as follows:
+     a) Create nodes for recurring organizations, people, and significant events, connecting them to the current node.
+     b) Store most facts as observations within these nodes
+   - Try to perform all updates in one operation using the create and delete functions.
+```