Memory
ECOSYSTEM REFERENCENO AUTHApache-2.0Open SourceSource: @agenticmarket· community reference
Give your AI assistant persistent memory across conversations. The Memory server stores entities, relations, and observations in a local knowledge graph that persists between sessions.
Setup Guide
{
"mcpServers": {
"memory-mcp-server": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}Tools
create_entities
Creates multiple entities in the knowledge graph by defining their names, types, and initial observations, enabling structured data representation from the start.
create_relations
Establishes directed relationships between existing entities using active-voice relation types to define clear semantic connections.
add_observations
Adds new factual observations or attributes to existing entities, enriching their stored information within the graph.
delete_entities
Deletes specified entities from the graph along with all associated relationships, ensuring complete removal of their connections.
delete_observations
Removes specific observations or facts from entities without affecting the entities themselves.
delete_relations
Removes specific directed relationships between entities without deleting the entities.
read_graph
Retrieves the full knowledge graph, including all entities and their relationships, providing a complete structural view.
search_nodes
Searches entities based on query strings across names, types, and observations to find relevant nodes in the graph.
open_nodes
Fetches specific entities by name along with their related connections and inter-relationships for detailed inspection.
Compatibility
About
The Memory MCP Server is part of the official MCP server collection maintained by Anthropic. It provides persistent memory across conversations using a local knowledge graph — giving your AI assistant the ability to remember facts, people, preferences, and relationships between sessions.
How it works
The server stores a knowledge graph in a local JSONL file with three primitives:
Entities — Named nodes with a type and observations:
json{ "name": "John_Smith", "entityType": "person", "observations": ["Speaks fluent Spanish", "Prefers dark mode"] }
Relations — Directed connections between entities:
json{ "from": "John_Smith", "to": "Acme_Corp", "relationType": "works_at" }
Observations — Atomic facts attached to entities. One fact per observation keeps things clean and deletable.
Custom storage location
By default, the knowledge graph is stored as memory.jsonl in the server's working directory. To use a specific path:
json{ "mcpServers": { "memory": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-memory"], "env": { "MEMORY_FILE_PATH": "/Users/you/.ai-memory/memory.jsonl" } } } }
This is useful when you want multiple AI tools to share the same memory file, or when you want to back up your knowledge graph with your dotfiles.
Prompting for better memory
The server works best when the AI is instructed to actively use it. Add instructions to your system prompt or Claude Project:
Follow these steps for each interaction:
1. Always begin by retrieving relevant information from your memory
2. While conversing, note new information about:
- People and their preferences
- Project requirements and decisions
- Technical choices and their rationale
3. After each interaction, update memory with any new facts learned
Docker installation
json{ "mcpServers": { "memory": { "command": "docker", "args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"] } } }
The Docker volume claude-memory persists the knowledge graph between container restarts.
Common issues
Memory resets between sessions
Check that MEMORY_FILE_PATH points to a persistent location. If you're using npx without setting this, the file may be created in a temporary directory that gets cleaned up.
"Entity not found" errors
Entity names are case-sensitive. John_Smith and john_smith are different entities. Use consistent naming conventions.
Graph getting too large The server loads the entire graph into memory. For very large knowledge graphs (10,000+ entities), searches may slow down. Periodically prune outdated entities.
Install and Troubleshooting Intent Coverage
Developer-install and troubleshooting intent for community MCP server listings.
install mcp server / mcp server setup guide
mcp json config example / vscode mcp setup
mcp server not working / mcp tools not showing
mcp server compatibility matrix / cursor vs vscode mcp compatibility
mcp server monetization options / convert community mcp server to paid listing
Related Setup, Debug, and Learning Links
CLI installation guide
Install baseline for all IDEs before listing-specific setup.
Using servers guide
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Cursor setup walkthrough
High-intent setup path for developer troubleshooting journeys.
Troubleshooting: server not working
Common failure modes for install and runtime issues.
Troubleshooting: tools not showing
Covers discovery/listing failures across major IDEs.
Related explore entry: FreshContext
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Related explore entry: Sequential Thinking
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Related explore entry: Everything MCP Server
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Install this server instantly with the AgenticMarket CLI — zero config, auto-detects your IDE.
$npx agenticmarket install memory-mcp-serverFreshContext
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Roundtable MCP
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