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Description
CMEM Cloud serves as the synchronization layer for claude-mem, designed to connect AI agent memory universally via a single private MCP link. The open-source engine, claude-mem, records notes while an agent performs tasks, while CMEM Cloud replicates that local memory, enabling agents to access it seamlessly across different sessions, devices, editors, and any MCP-compatible client. This innovative system eliminates the need for users to repetitively clarify context, copy previous notes, or start from scratch by automatically logging decisions, bug fixes, dead ends, environmental observations, architectural decisions, and other structured insights as the agent operates. These valuable insights are preserved in a temporal database, allowing for meaning-based searches through vector recall, and are accessible via a private MCP endpoint that any compatible agent can utilize for reading and writing. The process initiates with the installation of the local engine, followed by allowing a secondary model to generate structured notes independently, syncing the local database with CMEM Cloud, and finally enabling memory recall from any location. This approach not only enhances efficiency but also fosters a more collaborative environment among agents by sharing insights effortlessly.
Description
Engram is an advanced, fully managed service designed to enhance memory and context for AI agents, enabling them to retain, learn, and evolve effectively over time. Rather than accumulating an unmanageable collection of unstructured conversations and events, it meticulously transforms chaotic interaction data into well-organized, lasting, and adaptive memories. Applications can seamlessly transmit raw text, entire dialogues, or pre-processed facts via a REST API or Python SDK with no need for prior formatting. Engram then operates asynchronous processes that extract pertinent information, streamline it by removing duplicates and aligning it with existing knowledge, resulting in a refined memory state that does not interfere with the main operations of the application. It addresses inconsistencies, adjusts to evolving preferences and changing information over time, ensuring that the context remains both relevant and efficient. Additionally, agents have the capability to access prioritized memories instantly through vector similarity, BM25 keyword searches, or a combination of retrieval methods, thereby minimizing the necessity to resend complete conversation logs. This approach significantly enhances the efficiency and effectiveness of interactions, making AI agents more responsive and capable of understanding user needs.
API Access
Has API
API Access
Has API
Integrations
Claude Code
Codex CLI
Cursor
Devin Desktop
Gemini CLI
Model Context Protocol (MCP)
OpenCode
Python
Weaviate
claude-mem
Integrations
Claude Code
Codex CLI
Cursor
Devin Desktop
Gemini CLI
Model Context Protocol (MCP)
OpenCode
Python
Weaviate
claude-mem
Pricing Details
Free
Free Trial
Free Version
Pricing Details
$45 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
cmem.ai
Country
United States
Website
cmem.ai/
Vendor Details
Company Name
Weaviate
Founded
2019
Country
The Netherlands
Website
weaviate.io/product/engram