mcp-knowledge-graph
- Knowledge & Memory
An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.
Prompts
Interactive templates invoked by user choice
Name | Description |
---|---|
No prompts |
Resources
Contextual data attached and managed by the client
Name | Description |
---|---|
No resources |
Tools
Functions exposed to the LLM to take actions
Name | Description |
---|---|
create_entities | Create multiple new entities in the knowledge graph |
create_relations | Create multiple new relations between entities in the knowledge graph. Relations should be in active voice |
add_observations | Add new observations to existing entities in the knowledge graph |
delete_entities | Delete multiple entities and their associated relations from the knowledge graph |
delete_observations | Delete specific observations from entities in the knowledge graph |
delete_relations | Delete multiple relations from the knowledge graph |
read_graph | Read the entire knowledge graph |
search_nodes | Search for nodes in the knowledge graph based on a query |
open_nodes | Open specific nodes in the knowledge graph by their names |
Server Configuration
Describes the environment variables required to run the server.
Name | Required | Description | Default |
---|---|---|---|
No arguments |
Knowledge Graph Memory Server
An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path
.
This lets Claude remember information about the user across chats.
[!NOTE] This is a fork of the original Memory Server and is intended to not use the ephemeral memory npx installation method.
Server Name
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:
Custom Memory Path
You can specify a custom path for the memory file:
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.
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.
GitHub Badge
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