Graphiti

Overview

Graphiti is an open-source framework for building and querying temporally-aware knowledge graphs, specifically designed for AI agents operating in dynamic environments. It powers the core memory system in Zep's context engineering platform.

Key Features

• Temporal Awareness: Tracks when facts were true with explicit validity intervals (t_valid, t_invalid)
• Bi-Temporal Model: Stores both event time (when something happened) and ingestion time (when it was recorded)
• Dynamic Updates: Continuously integrates user interactions and enterprise data without batch recomputation
• Hybrid Search: Combines semantic search, keyword matching, and graph traversal
• Real-Time Processing: Incrementally processes incoming data with instant entity and relationship updates
• Low Latency: Precise queries without LLM summarization overhead

Architecture

Every graph edge (relationship) in Graphiti includes:

• Explicit validity intervals for temporal reasoning
• Relationship metadata and context
• Source attribution for traceability

The framework maintains communities of related entities that evolve over time.

Integration

Model Context Protocol (MCP)

Graphiti includes an MCP server, enabling integration with:

• Claude (Anthropic)
• Cursor IDE
• Other MCP-compatible clients

Supported Backends

• Neo4j (primary graph database)
• OpenAI (embeddings and LLM)
• Azure OpenAI
• Google Gemini
• Anthropic Claude

Performance

In the Deep Memory Retrieval (DMR) benchmark, Graphiti-powered systems achieve 94.8% accuracy versus 93.4% for MemGPT, demonstrating superior performance in memory retrieval tasks.

Use Cases

• AI agent memory systems
• Conversational AI with historical context
• Enterprise knowledge management
• Temporal reasoning applications
• Dynamic relationship tracking
• Multi-source data integration

Pricing

Free and open-source under the Apache 2.0 license.