A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats and learn from past errors through a lesson 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:

{
  "name": "John_Smith",
  "entityType": "person",
  "observations": ["Speaks fluent Spanish"]
}

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:

{
  "from": "John_Smith",
  "to": "Anthropic",
  "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:

{
  "entityName": "John_Smith",
  "observations": [
    "Speaks fluent Spanish",
    "Graduated in 2019",
    "Prefers morning meetings"
  ]
}

Lessons

Lessons are special entities that capture knowledge about errors and their solutions. Each lesson has: - A unique name (identifier) - Error pattern information (type, message, context) - Solution steps and verification - Success rate tracking - Environmental context - Metadata (severity, timestamps, frequency)

Example:

{
  "name": "NPM_VERSION_MISMATCH_01",
  "entityType": "lesson",
  "observations": [
    "Error occurs when using incompatible package versions",
    "Affects Windows environments specifically",
    "Resolution requires version pinning"
  ],
  "errorPattern": {
    "type": "dependency",
    "message": "Cannot find package @shadcn/ui",
    "context": "package installation"
  },
  "metadata": {
    "severity": "high",
    "environment": {
      "os": "windows",
      "nodeVersion": "18.x"
    },
    "createdAt": "2025-02-13T13:21:58.523Z",
    "updatedAt": "2025-02-13T13:22:21.336Z",
    "frequency": 1,
    "successRate": 1.0
  },
  "verificationSteps": [
    {
      "command": "pnpm add shadcn@latest",
      "expectedOutput": "Successfully installed shadcn",
      "successIndicators": ["added shadcn"]
    }
  ]
}

API

Tools

create_entities
Create multiple new entities in the knowledge graph
Input: entities (array of objects)
- Each object contains:
- name (string): Entity identifier
- entityType (string): Type classification
- observations (string[]): Associated observations
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 name
- to (string): Target entity name
- relationType (string): Relationship type in active voice
Skips duplicate relations
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

Lesson Management Tools

create_lesson
Create a new lesson from an error and its solution
Input: lesson (object)
- Contains:
- name (string): Unique identifier
- entityType (string): Must be "lesson"
- observations (string[]): Notes about the error and solution
- errorPattern (object): Error details
  - type (string): Category of error
  - message (string): Error message
  - context (string): Where error occurred
  - stackTrace (string, optional): Stack trace
- metadata (object): Additional information
  - severity ("low" | "medium" | "high" | "critical")
  - environment (object): System details
  - frequency (number): Times encountered
  - successRate (number): Solution success rate
- verificationSteps (array): Solution verification
  - Each step contains:
  - command (string): Action to take
  - expectedOutput (string): Expected result
  - successIndicators (string[]): Success markers
Automatically initializes metadata timestamps
Validates all required fields
find_similar_errors
Find similar errors and their solutions
Input: errorPattern (object)
- Contains:
- type (string): Error category
- message (string): Error message
- context (string): Error context
Returns matching lessons sorted by success rate
Uses fuzzy matching for error messages
update_lesson_success
Update success tracking for a lesson
Input:
- lessonName (string): Lesson to update
- success (boolean): Whether solution worked
Updates:
- Success rate (weighted average)
- Frequency counter
- Last update timestamp
get_lesson_recommendations
Get relevant lessons for current context
Input: context (string)
Searches across:
- Error type
- Error message
- Error context
- Lesson observations
Returns lessons sorted by:
- Context relevance
- Success rate
Includes full solution details

File Management

The server now handles two types of files: - memory.json: Stores basic entities and relations - lesson.json: Stores lesson entities with error patterns

Files are automatically split if they exceed 1000 lines to maintain performance.

Cursor MCP Client Setup

To integrate this memory server with Cursor MCP client, follow these steps:

Clone the Repository:

git clone [repository-url]
cd [repository-name]

Install Dependencies:
```
pnpm install
```
Build the Project:
```
pnpm build
```
Configure the Server:
Locate the full path to the built server file: /path/to/the/dist/index.js
Start the server using Node.js: node /path/to/the/dist/index.js
Activate in Cursor:
Use the keyboard shortcut Ctrl+Shift+P
Type "reload window" and select it
Wait a few seconds for the MCP server to activate
Select the stdio type when prompted

The memory server should now be integrated with your Cursor MCP client and ready to use.

Usage with Claude Desktop

Setup

Add this to your claude_desktop_config.json:

Docker

{
  "mcpServers": {
    "memory": {
      "command": "docker",
      "args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"]
    }
  }
}

NPX

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

NPX with custom setting

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)

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.

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

Building

Docker:

docker build -t mcp/memory -f src/memory/Dockerfile .

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.

New Tools

create_lesson
Create a new lesson from an error and its solution
Input: lesson (object)
- Contains error pattern, solution steps, and metadata
- Automatically tracks creation time and updates
- Verifies solution steps are complete
find_similar_errors
Find similar errors and their solutions
Input: errorPattern (object)
- Contains error type, message, and context
- Returns matching lessons sorted by success rate
- Includes related solutions and verification steps
update_lesson_success
Update success tracking for a lesson
Input:
- lessonName (string): Lesson to update
- success (boolean): Whether solution worked
Updates success rate and frequency metrics
get_lesson_recommendations
Get relevant lessons for current context
Input: context (string)
Returns lessons sorted by relevance and success rate
Includes full solution details and verification steps

BIG CREDITS TO THE OWNER OF THIS REPO FOR THE BASE CODE I ENHANCED IT WITH LESSONS AND FILE MANAGEMENT

Big thanks! https://github.com/modelcontextprotocol/servers jerome3o-anthropic https://github.com/modelcontextprotocol/servers/tree/main/src/memory

[
  {
    "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"
  },
  {
    "description": "Create a new lesson from an error and its solution",
    "inputSchema": {
      "properties": {
        "lesson": {
          "properties": {
            "entityType": {
              "description": "Must be 'lesson'",
              "enum": [
                "lesson"
              ],
              "type": "string"
            },
            "errorPattern": {
              "properties": {
                "context": {
                  "description": "Where the error occurred",
                  "type": "string"
                },
                "message": {
                  "description": "The error message",
                  "type": "string"
                },
                "stackTrace": {
                  "description": "Optional stack trace",
                  "type": "string"
                },
                "type": {
                  "description": "Category of the error",
                  "type": "string"
                }
              },
              "required": [
                "type",
                "message",
                "context"
              ],
              "type": "object"
            },
            "metadata": {
              "properties": {
                "environment": {
                  "properties": {
                    "dependencies": {
                      "additionalProperties": {
                        "type": "string"
                      },
                      "type": "object"
                    },
                    "nodeVersion": {
                      "type": "string"
                    },
                    "os": {
                      "type": "string"
                    }
                  },
                  "type": "object"
                },
                "severity": {
                  "description": "Severity level of the error",
                  "enum": [
                    "low",
                    "medium",
                    "high",
                    "critical"
                  ],
                  "type": "string"
                }
              },
              "type": "object"
            },
            "name": {
              "description": "Unique identifier for the lesson",
              "type": "string"
            },
            "observations": {
              "description": "List of observations about the error and solution",
              "items": {
                "type": "string"
              },
              "type": "array"
            },
            "verificationSteps": {
              "items": {
                "properties": {
                  "command": {
                    "description": "Command to run",
                    "type": "string"
                  },
                  "expectedOutput": {
                    "description": "Expected output",
                    "type": "string"
                  },
                  "successIndicators": {
                    "description": "Indicators of success",
                    "items": {
                      "type": "string"
                    },
                    "type": "array"
                  }
                },
                "required": [
                  "command",
                  "expectedOutput",
                  "successIndicators"
                ],
                "type": "object"
              },
              "type": "array"
            }
          },
          "required": [
            "name",
            "entityType",
            "observations",
            "errorPattern",
            "verificationSteps"
          ],
          "type": "object"
        }
      },
      "required": [
        "lesson"
      ],
      "type": "object"
    },
    "name": "create_lesson"
  },
  {
    "description": "Find similar errors and their solutions in the knowledge graph",
    "inputSchema": {
      "properties": {
        "errorPattern": {
          "properties": {
            "context": {
              "description": "Where the error occurred",
              "type": "string"
            },
            "message": {
              "description": "The error message",
              "type": "string"
            },
            "type": {
              "description": "Category of the error",
              "type": "string"
            }
          },
          "required": [
            "type",
            "message",
            "context"
          ],
          "type": "object"
        }
      },
      "required": [
        "errorPattern"
      ],
      "type": "object"
    },
    "name": "find_similar_errors"
  },
  {
    "description": "Update the success rate of a lesson after applying its solution",
    "inputSchema": {
      "properties": {
        "lessonName": {
          "description": "Name of the lesson to update",
          "type": "string"
        },
        "success": {
          "description": "Whether the solution was successful",
          "type": "boolean"
        }
      },
      "required": [
        "lessonName",
        "success"
      ],
      "type": "object"
    },
    "name": "update_lesson_success"
  },
  {
    "description": "Get relevant lessons based on the current context",
    "inputSchema": {
      "properties": {
        "context": {
          "description": "The current context to find relevant lessons for",
          "type": "string"
        }
      },
      "required": [
        "context"
      ],
      "type": "object"
    },
    "name": "get_lesson_recommendations"
  }
]

memories with lessons mcp server

Core Concepts

Entities

Relations

Observations

Lessons

API

Tools

Lesson Management Tools

File Management

Cursor MCP Client Setup

Usage with Claude Desktop

Setup

Docker

NPX

NPX with custom setting

System Prompt

Building

License

New Tools

BIG CREDITS TO THE OWNER OF THIS REPO FOR THE BASE CODE I ENHANCED IT WITH LESSONS AND FILE MANAGEMENT