CMEM Cloud

CMEM Cloud

cmem.ai
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About

CMEM Cloud is the cloud sync layer for claude-mem, built to link AI agent memory everywhere through one private MCP link. claude-mem is the open source engine that takes notes while an agent works, and CMEM Cloud mirrors that local memory so agents can recall it across every session, machine, editor, and MCP-compatible client. Instead of making users re-explain context, paste old notes, or restart from zero, the system captures decisions, bug fixes, dead ends, environment notes, architecture choices, and other structured observations as the agent works. Those observations are stored in a temporal database, searched by meaning through vector recall, and made available through a private MCP endpoint that any compatible agent can read and write through. It starts with installing the local engine, letting a second model write structured notes out of band, syncing the local database to CMEM Cloud, and then recalling that memory anywhere.

About

Maximem is an AI context management and memory platform designed to give generative AI systems a persistent, secure memory layer that retains and organizes information across conversations, applications, and models. Large language models typically operate with limited session memory, meaning they lose context between interactions and require users to repeatedly provide the same background information. Maximem addresses this limitation by creating a private memory vault that stores relevant context, preferences, historical data, and workflow information so AI systems can reference it in future interactions. It operates between AI models and applications, ensuring that conversations, knowledge, and user data are consistently available across different tools and sessions. This persistent memory allows AI assistants to deliver responses that are more personalized, accurate, and context-aware because the system can retrieve previously stored information.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI coding-agent users and developer teams who need offline-first cloud memory to sync project context, decisions, fixes, and semantic recall across agents, editors, machines, and MCP workflows

Audience

AI developers, professionals, and power users needing a generative AI system to retain persistent context and memory across multiple conversations, tools, and models

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

cmem.ai
United States
cmem.ai/

Company Information

Maximem
Founded: 2025
United States
www.maximem.ai/

Alternatives

claude-mem

claude-mem

cmem.ai

Alternatives

Hindsight

Hindsight

Vectorize
Hindsight

Hindsight

Vectorize
MemMachine

MemMachine

MemVerge
MemClaw

MemClaw

Caura AI
myNeutron

myNeutron

Vanar Chain

Categories

Categories

Integrations

ChatGPT
Claude Code
Codex CLI
Cursor
Devin Desktop
Gemini
Gemini CLI
Google Chrome
Model Context Protocol (MCP)
OpenClaw
OpenCode
Perplexity
claude-mem

Integrations

ChatGPT
Claude Code
Codex CLI
Cursor
Devin Desktop
Gemini
Gemini CLI
Google Chrome
Model Context Protocol (MCP)
OpenClaw
OpenCode
Perplexity
claude-mem
Claim CMEM Cloud and update features and information
Claim CMEM Cloud and update features and information
Claim Maximem and update features and information
Claim Maximem and update features and information