add_observations

Add new observations to existing entities

Input: observations (array of objects)

Each object contains:
entityName (string): Target entity
contents (string[]): New observations to add

Returns added observations per entity

Fails if entity doesn't exist

delete_entities

Remove entities and their relations

Input: entityNames (string[])

Cascading deletion of associated relations

Silent operation if entity doesn't exist

delete_observations

Remove specific observations from entities

Input: deletions (array of objects)

Each object contains:
entityName (string): Target entity
observations (string[]): Observations to remove

Silent operation if observation doesn't exist

delete_relations

Remove specific relations from the graph

Input: relations (array of objects)

Each object contains:
from (string): Source entity name
to (string): Target entity name
relationType (string): Relationship type

Silent operation if relation doesn't exist

read_graph

Read the entire knowledge graph

No input required

Returns complete graph structure with all entities and relations

search_nodes

Search for nodes based on query

Input: query (string)

Searches across:

Entity names
Entity types
Observation content

Returns matching entities and their relations

open_nodes

Retrieve specific nodes by name

Input: names (string[])

Returns:

Requested entities
Relations between requested entities

Silently skips non-existent nodes

Usage with Claude Desktop

Setup

Add this to your claude_desktop_config.json:

json { "mcpServers": { "memory": { "command": "npx", "args": [ "-y", "@modelcontextprotocol/server-memory" ] } } }

Custom Memory Path

You can specify a custom path for the memory file:

json { "mcpServers": { "memory": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-memory", "--memory-path", "/path/to/your/memory.jsonl"] } } }

If no path is specified, it will default to memory.jsonl in the server's installation directory.

System Prompt

The prompt for utilizing memory depends on the use case. Changing the prompt will help the model determine the frequency and types of memories created.

Here is an example prompt for chat personalization. You could use this prompt in the "Custom Instructions" field of a Claude.ai Project.

```txt Follow these steps for each interaction:

User Identification:
You should assume that you are interacting with default_user
If you have not identified default_user, proactively try to do so.
Memory Retrieval:
Always begin your chat by saying only "Remembering..." and retrieve all relevant information from your knowledge graph
Always refer to your knowledge graph as your "memory"
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, et

Categories

Current Category: ai-memory

mcp-knowledge-graph

the-pensieve