Memory MCP Server - Knowledge Graph

Persistent memory and knowledge graph for AI agents. Store entities, relations, and observations that persist across sessions.

Features

• Entities - Store named nodes with types and observations
• Relations - Connect entities with directional relationships
• Observations - Attach discrete facts to entities
• Search - Find entities by name, type, or observation content
• Persistence - Memory persists in Apify Key-Value Store
• Multi-tenant - Separate memory spaces using memoryKey

Tools

Tool	Description
memory.create_entities	Create new entities in the graph
memory.create_relations	Create relations between entities
memory.add_observations	Add facts to existing entities
memory.delete_entities	Remove entities (cascades relations)
memory.delete_observations	Remove specific observations
memory.delete_relations	Remove specific relations
memory.read_graph	Get complete graph with all data
memory.search_nodes	Search entities by query
memory.open_nodes	Get specific entities by name

Data Model

Entity

{
  "name": "John Doe",
  "entityType": "person",
  "observations": [
    "Works at Acme Corp",
    "Lives in New York",
    "Prefers email communication"
  ]
}

Relation

{
  "from": "John Doe",
  "to": "Acme Corp",
  "relationType": "works_at"
}

Examples

Create Entities

{
  "tool": "memory.create_entities",
  "memoryKey": "my-project",
  "entities": "[{\"name\": \"Alice\", \"entityType\": \"person\", \"observations\": [\"Team lead\", \"Prefers Slack\"]}]"
}

Create Relations

{
  "tool": "memory.create_relations",
  "memoryKey": "my-project",
  "relations": "[{\"from\": \"Alice\", \"to\": \"Engineering Team\", \"relationType\": \"leads\"}]"
}

Add Observations

{
  "tool": "memory.add_observations",
  "memoryKey": "my-project",
  "entityName": "Alice",
  "observations": "[\"Recently promoted\", \"Working on Q4 roadmap\"]"
}

Search Nodes

{
  "tool": "memory.search_nodes",
  "memoryKey": "my-project",
  "searchQuery": "engineering"
}

Read Full Graph

{
  "tool": "memory.read_graph",
  "memoryKey": "my-project"
}

Use Cases

• Personal Assistant Memory - Remember user preferences, contacts, projects
• CRM Knowledge Base - Store customer information and relationships
• Project Context - Track team members, decisions, and dependencies
• Research Notes - Connect concepts, papers, and findings
• Conversation History - Persist important facts across chat sessions

Memory Keys

Use memoryKey to create separate memory spaces:

• user-123 - Per-user memory
• project-alpha - Per-project memory
• session-xyz - Per-session memory

Memory persists in Apify Key-Value Store under key memory_{memoryKey}.

MCP Integration

Works with Claude Desktop, VS Code, and any MCP-compatible agent.

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "memory": {
      "url": "https://mcp.apify.com?actors=YOUR_USERNAME/memory-mcp-server"
    }
  }
}

System Prompt Example

Add to your AI agent's system prompt:

You have access to a persistent memory system. At the start of each conversation:
1. Use memory.read_graph to recall what you know about the user
2. As you learn new information, use memory.create_entities and memory.add_observations to save it
3. Use memory.create_relations to connect related concepts

Important information to remember:
- User's name, preferences, and goals
- Projects they're working on
- People and organizations they mention
- Decisions and agreements made

Pricing

Apify compute costs only. No external API required.

Limits

Limit	Value
Max entities	10,000
Max observations per entity	1,000
Max observation length	10,000 chars
Memory file size	10 MB

Support

For issues or feature requests, open a ticket on the Issues tab.