The Knowledge Graph Memory Server provides persistent memory for Claude using a local knowledge graph, enabling memory across chats. With this server, you can:
Create entities: Add nodes with unique names, types, and observations
Create relations: Define directed relationships between entities
Add observations: Append new facts to existing entities
Delete entities: Remove nodes and their associated relations
Delete observations: Remove specific facts from entities
Delete relations: Remove specific connections between entities
Read graph: Retrieve the entire knowledge graph structure
Search nodes: Find entities by querying names, types, or observation content
Open nodes: Retrieve specific entities and their relations by name
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.
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:
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:
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:
API
Tools
- create_entities
- Create multiple new entities in the knowledge graph
- Input:
entities
(array of objects)- Each object contains:
name
(string): Entity identifierentityType
(string): Type classificationobservations
(string[]): Associated observations
- Each object contains:
- 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 nameto
(string): Target entity namerelationType
(string): Relationship type in active voice
- Each object contains:
- Skips duplicate relations
- add_observations
- Add new observations to existing entities
- Input:
observations
(array of objects)- Each object contains:
entityName
(string): Target entitycontents
(string[]): New observations to add
- Each object contains:
- 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 entityobservations
(string[]): Observations to remove
- Each object contains:
- 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 nameto
(string): Target entity namerelationType
(string): Relationship type
- Each object contains:
- 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:
Docker
NPX
NPX with custom setting
The server can be configured using the following environment variables:
MEMORY_FILE_PATH
: Path to the memory storage JSON file (default:memory.json
in the server directory)
VS Code Installation Instructions
For quick installation, use one of the one-click installation buttons below:
For manual installation, you can configure the MCP server using one of these methods:
Method 1: User Configuration (Recommended)
Add the configuration to your user-level MCP configuration file. Open the Command Palette (Ctrl + Shift + P
) and run MCP: Open User Configuration
. This will open your user mcp.json
file where you can add the server configuration.
Method 2: Workspace Configuration
Alternatively, you can add the configuration to a file called .vscode/mcp.json
in your workspace. This will allow you to share the configuration with others.
For more details about MCP configuration in VS Code, see the official VS Code MCP documentation.
NPX
Docker
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.
Building
Docker:
For Awareness: a prior mcp/memory volume contains an index.js file that could be overwritten by the new container. If you are using a docker volume for storage, delete the old docker volume's index.js
file before starting the new container.
License
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
local-only server
The server can only run on the client's local machine because it depends on local resources.
Tools
A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.
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