CoreMemory-MCP

Store the following in long-term memory: I prefer concise answers, Chinese by default, and Python examples for code-related topics. At the start of future sessions, retrieve and apply these preferences.

The AI confirms the preferences were saved and can retrieve and apply them in later sessions.

Write this project context into long-term memory: Our product is a SaaS expense reimbursement system for SMBs, targeting finance and admin teams, and the current focus is improving approval efficiency. Recall this context before answering related questions later.

The AI stores the project context and automatically uses it in later analysis, copywriting, or planning discussions.

Search long-term memory for records about 'user interview findings' and 'approval workflow pain points', summarize them into bullet points, and mark which items can be directly used for the current solution design.

Returns a summary of relevant past records, key pain points, and conclusions reusable for the current task.