Memary

At a glance

• Editor score
  6.1 / 10
• Pricing
  Free plan
• Best for
  Self-hosted agents needing graph and persona memory
• Free plan
  Yes
• Paid from
  None
• Semantic memory
  Yes
• Facts checked
  13 Oct 2026

• Where it wins

  • Automatically captures timestamped memories and updates them during interactions
  • Combines frequency, recency, and multi-hop graph retrieval
  • Connects with FalkorDB, Neo4j, Ollama, OpenAI, and tool services

• Where it doesn't

  • Self-hosted deployment requires managing the runtime and storage environment
  • Python-focused package may not fit teams seeking multi-language SDKs
  • Retention controls are not part of the documented feature set

Our verdict on Memary

Memary is an open-source Python memory layer for autonomous agents. It targets developers building self-hosted agents that need more than a simple chat-history buffer, including semantic, episodic, graph, and user-profile memory. The package captures entities and timestamps from interactions, tracks user personas and preferences, summarizes chat history, and manages context-window information. A Streamlit interface and a ReAct-based agent provide an interactive surface for teams working in web-based environments.

Its standout capability is the combination of a timestamped Memory Stream, an Entity Knowledge Store, and graph-backed retrieval. Memories can be ranked by frequency and recency, while recursive and multi-hop retrieval follows relationships across a knowledge graph. FalkorDB supports multi-agent graphs, and Neo4j is another graph backend. The integration set also includes local Ollama models, OpenAI, Perplexity, Google Maps, Alpha Vantage, LlamaIndex, and Streamlit. Optional search, vision, location, and stock tools extend the included ReAct agent beyond memory retrieval.

Memary is installed with pip or from its repository and run in the developer’s own environment, so teams choose and operate the surrounding model and database services themselves. That approach suits solo developers and small or mid-market teams that want control over deployment and an MIT-licensed codebase. It is less suitable for buyers seeking a hosted service, turnkey operations, or a broad set of language-specific SDKs. Choose Memary when graph relationships, persona tracking, and self-managed infrastructure are central requirements; consider another tool when managed deployment is the priority.

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Memary pricing

Memary fact sheet

Memary integrations

Memary lists 9 integrations on its own site.

• FalkorDB
• Neo4j
• Ollama
• OpenAI
• Perplexity
• Google Maps
• Alpha Vantage
• LlamaIndex
• Streamlit

Alternatives to Memary

• CACloudflare Agent MemoryA cloud API for scoped, searchable memory across AI agent profiles and conversations.9.2
• MMem0A flexible memory layer with semantic, graph, and self-hosted deployment options.8.8
• MMMCP Memory ServiceA broad open-source memory layer for teams that can manage deployment and configuration.7.9

See all Memary alternatives →

Featured on iTechGuides

Memary is listed in our AI Agent Memory Tools directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 20 Oct 2026 · How we research and update