Knowsme

What knowsme does

knowsme stores a single body of context about who you are and how you work. That context is organized around three kinds of information: notes, rules, and projects. AI models and agents can access the memory through MCP rather than keeping relevant details only inside an individual chat or application.

The central use case is continuity. Information recorded for one app or machine can be available to another AI application that connects through MCP. This makes knowsme suitable for personal working context that needs to follow you between environments.

How it works

AI models and agents interact with knowsme over the Model Context Protocol. The connection provides two core operations: reading existing memory and updating it. Read access lets an agent use stored notes, rules, and project context while working. Update access lets an agent add or revise information so the shared memory can reflect changes over time.

The memory is presented as one shared source of information about the user and their working habits. Its cross-application and cross-machine purpose distinguishes it from context that exists only within a single model session.

Tools and capabilities

• Read stored notes, rules, and project information.
• Update the shared memory through MCP.
• Provide personal context to AI models and agents across apps.
• Keep working context available across machines.

Limitations and notes

knowsme is focused on personal memory rather than a general-purpose data service. Its stated memory model covers notes, rules, and projects, with information about who you are and how you work. An MCP-compatible model or agent is needed to interact with it. The value of the service depends on keeping shared context accurate when it is updated, since later applications may rely on the stored information.

The server is a fit when the goal is portable AI context. It is less clearly suited to use cases that require a different data model or capabilities outside reading and updating this personal memory.