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.
A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.
A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.
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:
{
"name": "John_Smith",
"entityType": "person",
"observations": ["Speaks fluent Spanish"]
}
Relations define directed connections between entities. They are always stored in active voice and describe how entities interact or relate to each other.
Example:
{
"from": "John_Smith",
"to": "Anthropic",
"relationType": "works_at"
}
Observations are discrete pieces of information about an entity. They are:
Example:
{
"entityName": "John_Smith",
"observations": [
"Speaks fluent Spanish",
"Graduated in 2019",
"Prefers morning meetings"
]
}
entities
(array of objects)name
(string): Entity identifierentityType
(string): Type classificationobservations
(string[]): Associated observationsIgnores entities with existing names
create_relations
relations
(array of objects)from
(string): Source entity nameto
(string): Target entity namerelationType
(string): Relationship type in active voiceSkips duplicate relations
add_observations
observations
(array of objects)entityName
(string): Target entitycontents
(string[]): New observations to addFails if entity doesn't exist
delete_entities
entityNames
(string[])Silent operation if entity doesn't exist
delete_observations
deletions
(array of objects)entityName
(string): Target entityobservations
(string[]): Observations to removeSilent operation if observation doesn't exist
delete_relations
relations
(array of objects)from
(string): Source entity nameto
(string): Target entity namerelationType
(string): Relationship typeSilent operation if relation doesn't exist
read_graph
Returns complete graph structure with all entities and relations
search_nodes
query
(string)Returns matching entities and their relations
open_nodes
names
(string[])Add this to your claude_desktop_config.json:
{
"mcpServers": {
"memory": {
"command": "docker",
"args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"]
}
}
}
{
"mcpServers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}
The server can be configured using the following environment variables:
{
"mcpServers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
],
"env": {
"MEMORY_FILE_PATH": "/path/to/custom/memory.json"
}
}
}
}
MEMORY_FILE_PATH
: Path to the memory storage JSON file (default: memory.json
in the server directory)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.
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 graph 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 (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 entities for recurring organizations, people, and significant events
b) Connect them to the current entities using relations
b) Store facts about them as observations
Docker:
docker build -t mcp/memory -f src/memory/Dockerfile .
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.
[
{
"description": "Create multiple new entities in the knowledge graph",
"inputSchema": {
"properties": {
"entities": {
"items": {
"properties": {
"entityType": {
"description": "The type of the entity",
"type": "string"
},
"name": {
"description": "The name of the entity",
"type": "string"
},
"observations": {
"description": "An array of observation contents associated with the entity",
"items": {
"type": "string"
},
"type": "array"
}
},
"required": [
"name",
"entityType",
"observations"
],
"type": "object"
},
"type": "array"
}
},
"required": [
"entities"
],
"type": "object"
},
"name": "create_entities"
},
{
"description": "Create multiple new relations between entities in the knowledge graph. Relations should be in active voice",
"inputSchema": {
"properties": {
"relations": {
"items": {
"properties": {
"from": {
"description": "The name of the entity where the relation starts",
"type": "string"
},
"relationType": {
"description": "The type of the relation",
"type": "string"
},
"to": {
"description": "The name of the entity where the relation ends",
"type": "string"
}
},
"required": [
"from",
"to",
"relationType"
],
"type": "object"
},
"type": "array"
}
},
"required": [
"relations"
],
"type": "object"
},
"name": "create_relations"
},
{
"description": "Add new observations to existing entities in the knowledge graph",
"inputSchema": {
"properties": {
"observations": {
"items": {
"properties": {
"contents": {
"description": "An array of observation contents to add",
"items": {
"type": "string"
},
"type": "array"
},
"entityName": {
"description": "The name of the entity to add the observations to",
"type": "string"
}
},
"required": [
"entityName",
"contents"
],
"type": "object"
},
"type": "array"
}
},
"required": [
"observations"
],
"type": "object"
},
"name": "add_observations"
},
{
"description": "Delete multiple entities and their associated relations from the knowledge graph",
"inputSchema": {
"properties": {
"entityNames": {
"description": "An array of entity names to delete",
"items": {
"type": "string"
},
"type": "array"
}
},
"required": [
"entityNames"
],
"type": "object"
},
"name": "delete_entities"
},
{
"description": "Delete specific observations from entities in the knowledge graph",
"inputSchema": {
"properties": {
"deletions": {
"items": {
"properties": {
"entityName": {
"description": "The name of the entity containing the observations",
"type": "string"
},
"observations": {
"description": "An array of observations to delete",
"items": {
"type": "string"
},
"type": "array"
}
},
"required": [
"entityName",
"observations"
],
"type": "object"
},
"type": "array"
}
},
"required": [
"deletions"
],
"type": "object"
},
"name": "delete_observations"
},
{
"description": "Delete multiple relations from the knowledge graph",
"inputSchema": {
"properties": {
"relations": {
"description": "An array of relations to delete",
"items": {
"properties": {
"from": {
"description": "The name of the entity where the relation starts",
"type": "string"
},
"relationType": {
"description": "The type of the relation",
"type": "string"
},
"to": {
"description": "The name of the entity where the relation ends",
"type": "string"
}
},
"required": [
"from",
"to",
"relationType"
],
"type": "object"
},
"type": "array"
}
},
"required": [
"relations"
],
"type": "object"
},
"name": "delete_relations"
},
{
"description": "Read the entire knowledge graph",
"inputSchema": {
"properties": {},
"type": "object"
},
"name": "read_graph"
},
{
"description": "Search for nodes in the knowledge graph based on a query",
"inputSchema": {
"properties": {
"query": {
"description": "The search query to match against entity names, types, and observation content",
"type": "string"
}
},
"required": [
"query"
],
"type": "object"
},
"name": "search_nodes"
},
{
"description": "Open specific nodes in the knowledge graph by their names",
"inputSchema": {
"properties": {
"names": {
"description": "An array of entity names to retrieve",
"items": {
"type": "string"
},
"type": "array"
}
},
"required": [
"names"
],
"type": "object"
},
"name": "open_nodes"
}
]