getzep/graphiti
Build Real-Time Knowledge Graphs for AI Agents observed · 2026-08-28
Health v2 · maintenance only
84/100
- Activity 99
- Release rhythm 83
- Longevity 53
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 1.0
- age_days: 755
- days_rel: 37
- days_push: 7
- n_releases_24m: 145
Adoption not part of the score
30324 stars · 3071 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Graphiti is an open-source Python framework for building and querying temporal knowledge graphs (Context Graphs) for AI agents. It incrementally ingests structured and unstructured data into graph databases like Neo4j and FalkorDB, tracking how facts change over time and supporting hybrid semantic, keyword, and graph-traversal retrieval.
Use cases
- build temporal knowledge graphs for AI agents
- give chatbots persistent memory across conversations
- replace flat RAG document chunks with structured context
- query evolving entity relationships with hybrid search
- connect a knowledge graph to Claude or Cursor via MCP
- personalize agent responses using learned user facts
- track historical facts and provenance in an agent memory layer
When to choose
- you need agent memory that updates incrementally without batch recomputation
- you want temporal awareness of when facts were valid, not just current state
- you need hybrid retrieval combining semantic, keyword, and graph traversal
- you want an MCP server to give IDE assistants persistent context
- you can run Neo4j, FalkorDB, Neptune, or Kuzu as a backend
When to avoid
- you need a fully managed memory service without operating a graph database (consider Zep Cloud)
- your retrieval needs are simple document search served well by a vector store
- you cannot use an LLM provider, since graph construction depends on LLM inference
- you need a non-Python SDK as the primary interface
Facets
framework · maturity active
rag agent-framework search-engine llm-inference mcp large-language-models databases graph-processing developer-tools python self-hosted cross-platform knowledge-graph temporal-graph agent-memory neo4j falkordb context-graph hybrid-search mcp-server graph ai-agents retrieval-augmented-generation docker
8 sources
- readme: https://github.com/getzep/graphiti · fetched 2026-08-28 · b903e99a59b7
- homepage: https://help.getzep.com/graphiti · fetched 2026-08-29 · ca504cfb7b87
- site_page: https://help.getzep.com/graphiti/getting-started/overview · fetched 2026-08-29 · b8367375b2ca
- site_page: https://help.getzep.com/graphiti/getting-started/quick-start · fetched 2026-08-29 · 818bb58e12ef
- site_page: https://help.getzep.com/graphiti/getting-started/mcp-server · fetched 2026-08-29 · defc06a91691
- site_page: https://help.getzep.com/concepts · fetched 2026-08-29 · aea70949e2d2
- site_page: https://help.getzep.com/changelog · fetched 2026-08-29 · 928712432c98
- site_page: https://help.getzep.com/graphiti/integrations/lang-graph-agent · fetched 2026-08-29 · 1378d250acdd
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| getzep/graphiti | main | 84 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem