Comparison
contexto vs mem0
Verdict
Pick contexto if contexto is a context engine for long-running AI agents, supporting OpenClaw and Hermes, with managed hosting options; pick mem0 if mem0 is a Python-based memory infrastructure for AI agents and applications, offering a persistent context layer suitable for production environments.
Markdown twin · contexto alternatives · mem0 alternatives
GraphCanon updated Sep 20, 2026
Trust & integrity
| Signal | contexto | mem0 |
|---|---|---|
| Maintenance | Slowing (100d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- contexto
- Context Engine for long-running AI agents
- mem0
- Drop-in memory infrastructure for AI agents and apps
Stars
- contexto
- 620
- mem0
- 66k
Forks
- contexto
- 22
- mem0
- 7.7k
Open issues
- contexto
- 21
- mem0
- 754
Language
- contexto
- TypeScript
- mem0
- Python
Adopt for
- contexto
- Contexto is a context engine for long-running AI agents, supporting OpenClaw and Hermes, with managed hosting options.
- mem0
- mem0 is a Python-based memory infrastructure for AI agents and applications, offering a persistent context layer suitable for production environments.
Persona
- contexto
- -
- mem0
- -
Runtime
- contexto
- -
- mem0
- -
License
- contexto
- Apache-2.0
- mem0
- mem0 is distributed under the Apache-2.0 license, allowing for broad usage and modification with attribution.
Last pushed
- contexto
- Jun 10, 2026
- mem0
- Sep 18, 2026
Categories
- contexto
- AI Agents, Data & Retrieval
- mem0
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- contexto
- Slowing (36%)
- mem0
- Very active (96%)
Days since push
- contexto
- 100d
- mem0
- 0d
Open issues (now)
- contexto
- 21
- mem0
- 754
Stars delta
- contexto
- -7 (30d)
- mem0
- +2.8k (30d)
Open issues delta
- contexto
- 0 (30d)
- mem0
- +63 (30d)
Full report
- contexto
- Trust report
- mem0
- Trust report
Choose contexto if…
- contexto is primarily TypeScript; mem0 is Python.
- Managed hosting is available, eliminating the need to run retrieval infrastructure yourself.
- Requirements: Built specifically for OpenClaw and Hermes..
- Tags unique to contexto: apache 2.0, context-engine, hermes, long-running agents.
- contexto ships Docker support for self-hosted deployment.
- When you are developing long-running AI agents that require reliable context management.
When NOT to use contexto
- If your AI agent does not require long-term context management or operates in short sessions.
- When you are not using OpenClaw or Hermes and prefer a context engine that supports a wider range of frameworks.
- If you need full control over your retrieval infrastructure and prefer not to use managed hosting services.
Choose mem0 if…
- mem0 is primarily Python; contexto is TypeScript.
- Pricing: The core functionality of mem0 is free to use under the Apache-2.0 license, but additional features or support might come at a cost..
- Requirements: Min 2 GB RAM; Python environment is required for installation and use..
- Tags unique to mem0: agentic-memory, ai-agents, genai, long-term-memory.
- When you need a persistent memory layer for AI agents that can be easily integrated into existing applications without significant changes.
When NOT to use mem0
- If your project is not in Python, as mem0 is specifically designed for Python environments.
- When you require a more customizable memory management system that allows for extensive configuration beyond what mem0 offers.
- If your application does not need a persistent memory layer or if the existing memory management solutions are sufficient.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ekailabs/contexto) · observed Sep 20, 2026
- GitHub forks (ekailabs/contexto) · observed Sep 20, 2026
- Last push (ekailabs/contexto) · observed Jun 10, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (mem0ai/mem0) · observed Sep 20, 2026
- GitHub forks (mem0ai/mem0) · observed Sep 20, 2026
- Last push (mem0ai/mem0) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: contexto 620 · mem0 66k (synced Sep 20, 2026).
Common questions
- What is the difference between contexto and mem0?
- contexto: Context Engine for long-running AI agents. mem0: Drop-in memory infrastructure for AI agents and apps. See the comparison table for live GitHub stats and shared categories.
- When should I choose contexto over mem0?
- Choose contexto over mem0 when contexto is primarily TypeScript; mem0 is Python; Managed hosting is available, eliminating the need to run retrieval infrastructure yourself; Requirements: Built specifically for OpenClaw and Hermes.; Tags unique to contexto: apache 2.0, context-engine, hermes, long-running agents; contexto ships Docker support for self-hosted deployment; When you are developing long-running AI agents that require reliable context management.
- When should I choose mem0 over contexto?
- Choose mem0 over contexto when mem0 is primarily Python; contexto is TypeScript; Pricing: The core functionality of mem0 is free to use under the Apache-2.0 license, but additional features or support might come at a cost.; Requirements: Min 2 GB RAM; Python environment is required for installation and use.; Tags unique to mem0: agentic-memory, ai-agents, genai, long-term-memory; When you need a persistent memory layer for AI agents that can be easily integrated into existing applications without significant changes.
- When should I avoid contexto?
- If your AI agent does not require long-term context management or operates in short sessions. When you are not using OpenClaw or Hermes and prefer a context engine that supports a wider range of frameworks. If you need full control over your retrieval infrastructure and prefer not to use managed hosting services.
- When should I avoid mem0?
- If your project is not in Python, as mem0 is specifically designed for Python environments. When you require a more customizable memory management system that allows for extensive configuration beyond what mem0 offers. If your application does not need a persistent memory layer or if the existing memory management solutions are sufficient.
- Is contexto or mem0 more popular on GitHub?
- mem0 has more GitHub stars (65,557 vs 620). Stars measure visibility, not whether either tool fits your constraints.
- Are contexto and mem0 open source?
- Yes - both are open-source projects on GitHub (contexto: Apache-2.0, mem0: Apache-2.0).
- Where can I find alternatives to contexto or mem0?
- GraphCanon lists graph-backed alternatives at contexto alternatives and mem0 alternatives (contexto markdown twin, mem0 markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, contexto or mem0?
- contexto: Slowing. mem0: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for contexto and mem0?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: contexto trust report; mem0 trust report.