#77th of 12 in Memory

Graphiti

Temporal knowledge graph framework for agent memory with REST and MCP servers

Stars
31.6k
License
Apache-2.0
Last commit
Oct 2026
Last release
Sep 2026
Language
Python

Overview

Graphiti builds context graphs where every fact has a validity window and traces back to its source episode, ingesting text and JSON incrementally. Retrieval fuses embeddings, BM25 and graph traversal. It needs a graph database (Neo4j, FalkorDB or Neptune) and defaults to OpenAI, with Anthropic, Gemini, Groq and OpenAI-compatible servers supported; REST and MCP servers ship in the repo.

Who it is for: Developers who want temporal graph memory and can run a graph database

Strengths

  • Bi-temporal facts: old facts are invalidated, not deleted, so history stays queryable
  • Hybrid retrieval combines embeddings, BM25 and graph traversal with sub-second latency claims
  • Custom entity and edge types via Pydantic models
  • Docker Compose profiles for Neo4j or FalkorDB; MCP and REST servers included

Weaknesses

  • Requires Neo4j, FalkorDB or Amazon Neptune plus OpenSearch; Kuzu is deprecated
  • Defaults to OpenAI; needs structured-output models, smaller models may fail ingestion
  • Default SEMAPHORE_LIMIT of 10 keeps ingestion slow to avoid 429 errors
  • Users, threads and dashboards are left to the commercial Zep platform

What it needs

  • no GPU
  • Docker + Compose
  • Needs Neo4j 5.26, FalkorDB 1.1.2 or Amazon Neptune
  • Models: OpenAI (default), Azure OpenAI, Anthropic, Google Gemini, Groq

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