Team Memory provides a team experience database, leveraging the MCP protocol to address the core limitation of AI programming assistants: their lack of memory across sessions. By automatically extracting, storing, and retrieving historical team knowledge, it ensures AI can understand project context, past decisions, and encountered pitfalls. This transforms AI assistants into more informed and effective collaborators who learn and grow with the team, bridging the gap between static knowledge and dynamic, implicit experiences gathered during development.
Key Features
01Semantic search for historical solutions and decisions
02Seamless integration with AI tools like Cursor and Claude via MCP
03Cross-session memory for AI programming assistants
04AI-powered experience extraction and storage
05Optional architecture visualization of project code structure
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Use Cases
01Sharing implicit knowledge within 3-10 person technical teams
02Local deployment for individual developers using AI assistants (e.g., Cursor, Claude Desktop)
03Enhancing AI programming assistants to understand project context and historical decisions
