About Memory MCP Server
Memory MCP Server is a Python server for storing and processing memory as a knowledge graph. It serves AI systems that need structured information across sessions, with tools to manage, search, and retrieve entities, relations, and observations.
Key features
- 01Create and manage entities
- 02Define typed entity relations
- 03Add or delete observations
- 04Search nodes and retrieve by name
- 05Read the full knowledge graph
Use cases
- 01Persist AI memory across sessions
- 02Organize entities and their relations
- 03Find or retrieve graph information
MCP support
The MCP server exposes knowledge graph tools for creating, searching, reading, and deleting entities, relations, and observations.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMemory MCP Server
A Python implementation of an MCP server that processes and saves memory in the form of a knowledge graph.
Overview
MCP Server Memory provides functionality for maintaining a persistent knowledge graph for AI memory. It allows storing, retrieving, and querying structured data in the form of entities, relations, and observations. This enables AI systems to store and recall information across sessions.
Features
- Create and manage entities with structured information
- Establish typed relations between entities
- Add observations to existing entities
- Delete entities, relations, and observations
- Search nodes in the knowledge graph
- Retrieve specific nodes by name
Tools
The server implements the MCP (Model Control Protocol) interface, exposing the following tools:
create_entities: Create multiple new entities in the knowledge graphcreate_relations: Create multiple new relations between entitiesadd_observations: Add new observations to existing entitiesdelete_entities: Delete entities and their associated relationsdelete_observations: Delete specific observations from entitiesdelete_relations: Delete specific relations from the graphread_graph: Read the entire knowledge graphsearch_nodes: Search for nodes matching a queryopen_nodes: Retrieve specific nodes by name
Installation
Using uv (recommended)
uv add mcp-server-memory
Using pip
pip install mcp-server-memory
Usage
Running the server
# Run the server directly
mcp-server-memory
# Set custom memory file path
MEMORY_FILE_PATH=/path/to/memory.json mcp-server-memory
Configuration
Configure for MCP clients
Add to your Claude(claude_desktop_config.json) or Cursor(mcp.json) settings file:
Using uv
"mcpServers": {
"memory": {
"command": "/path/to/uv",
"args": [
"--directory",
"/path/to/mcp_server_memory/src",
"run",
"python",
"-m",
"mcp_server_memory"
],
"env": {
"MEMORY_FILE_PATH": "/path/to/memory.json"
}
}
}
Using pip installation
"mcpServers": {
"memory": {
"command": "python",
"args": ["-m", "mcp_server_memory"]
}
}
Configuring the Memory Path
By default, the knowledge graph data is stored in a memory.json file in the package directory. You can customize the location using the MEMORY_FILE_PATH environment variable.
Development
Clone the repository and install development dependencies:
git clone https://github.com/jcdiv47/mcp-server-memory.git
cd mcp-server-memory
uv venv
source .venv/bin/activate
uv install -e ".[dev]"
License
mcp-server-memory 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.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.