Where is the memory data stored?
By default in `memory.json` in the server directory. You can change this by setting the `MEMORY_FILE_PATH` environment variable.
@s2005
Basic information
Standalone MCP server for enabling memory for Claude through a knowledge graph
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-memory-server": {
"command": "docker",
"args": [
"build",
"-t",
"mcp/memory",
"-f",
"src/Dockerfile",
"."
]
}
}
}Create multiple new entities in the knowledge graph
Create multiple new relations between entities
Add new observations to existing entities
Remove entities and their relations
Remove specific observations from entities
Remove specific relations from the graph
Read the entire knowledge graph
Search for nodes based on query
Retrieve specific nodes by name
A basic implementation of persistent memory using a local knowledge graph. It lets Claude remember information about the user across chats by storing entities, relations, and observations.
Add the server configuration to claude_desktop_config.json using Docker (recommended) or NPX. Optionally set the MEMORY_FILE_PATH environment variable to customize the storage location. Use the provided system prompt example in a Claude.ai Project to enable memory operations.
By default in `memory.json` in the server directory. You can change this by setting the `MEMORY_FILE_PATH` environment variable.
Add the Docker configuration from the README to `claude_desktop_config.json`. The Docker command mounts a volume `claude-memory` for persistence and runs the `mcp/memory` image.
Yes. Install the npm package `mcp-memory-server` or run directly with `npx mcp-memory-server`.
The server ignores duplicate entity names when using `create_entities`. Similarly, duplicate relations are skipped.
It is licensed under the MIT License.
High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 162 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

AI agents start every session with amnesia — you re-explain the project, repeat your preferences, and correct the same mistakes over and over. PLUR gives them a memory that persists. Your agent's corrections, preference
Project context your AI can query through MCP — with source evidence.

The official Semantic-UI-React integration
Shared, serverless, conflict-free memory for AI agents: a multi-machine drop-in for the MCP memory knowledge graph.
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