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AppRisingofficial publisher

Mem0

App : A product you use directly

Persistent memory layer for agents and assistants, hosted or self-hosted.

The most widely adopted memory component for giving continuity to an agent.

Official site GitHub · 67,757 ★
Overall score
7.6 /10
Security: one caveat, see the card
Utility
8.0
Reliability
10.0
Security
One caveat
Ease
5 min · Technical

Security reflects where data goes, requested permissions and incidents on record at the verification date. It is not a guarantee of zero risk: check the deployment mode and the connections you enable.

What it does, concretely

AI agents and assistants lose context between sessions: every conversation starts from scratch, with no memory of user preferences, history, or prior context. Mem0 solves this by adding a persistent memory layer that survives restarts and session changes.

In practice, Mem0 automatically extracts key facts from conversations, stores them as indexed memories, and retrieves them at the right moment using a search that combines semantic matching, keyword search (BM25), and entity linking. The algorithm updated in April 2026 works in a single LLM call with no agentic loop, reducing latency and token costs.

Mem0 is aimed at developers building agents, customer support chatbots, healthcare assistants, or productivity tools that need to remember users across sessions. The platform offers three modes: a Python/npm library for testing, a self-hosted Docker server for teams, and a managed cloud service for zero-ops production use.

Mem0 is not suited for non-technical end users looking for a ready-to-use application: it is primarily an infrastructure component for developers. In addition, the cloud service stores personal data by nature; for sensitive data, self-hosting is recommended.

What it offers

  • ·Multi-level memory: Mem0 independently retains user, session, and agent state.
  • ·Automatic fact extraction from conversations, with no manual configuration.
  • ·Hybrid search combining semantic similarity, keyword matching (BM25), and entity linking to retrieve relevant memories.
  • ·Temporal reasoning: retrieval is time-aware to distinguish past events, current state, and future plans.
  • ·Self-hosting via Docker with a dashboard, authentication, and API key management.
  • ·CLI available (npm or pip) to add and search memories directly from the terminal.
  • ·Integration with coding assistants (Claude Code, Cursor, Windsurf, Codex) via a skills system.
  • ·SOC 2 (Type 1), HIPAA, and GDPR compliance on the managed cloud platform. (paid)

In practice

Price
Freemium
Commercial use
Commercial use: yes
Available on
web, cli, claude-code
Licence
Apache-2.0

Security and data

Rating
Security: one caveat, see the card
Your data
Local or cloud depending on use
Maintenance
Active
Last release
25 September 2026

Links and repository checked on 25 October 2026 · added on 1 June 2024

How to install Mem0

1. Install the Python library: pip install mem0ai (or pip install mem0ai[nlp] for full hybrid search). 2. Get an API key at app.mem0.ai or, for an agent, via mem0 init --agent --agent-caller <name>. 3. Set the MEM0_API_KEY environment variable with your key (do not hard-code it in source files). 4. For self-hosting, navigate to the server folder and run make bootstrap to start the Docker stack and create an admin. 5. For sensitive data, prefer self-hosting so your data does not transit through Mem0 servers. 6. See the full documentation at docs.mem0.ai to configure your preferred LLM and embedding model.
pip install mem0ai

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