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Give MCP-compatible AI tools four-layer long-term memory for persistent context.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "TencentAgentMemoryBridge MCP Server" yet — see the docs or source repo.
Store this repository’s tech stack, module boundaries, coding conventions, and the refactoring decisions I just confirmed into long-term memory, and automatically use them in future coding suggestions.
The tool saves key project information into layered memory so future code suggestions follow prior context and conventions.
Remember my preferences: give the conclusion first, default to TypeScript, and use REST-style API naming; also save the product goals and constraints we discussed.
The tool stores preferences, facts, and scene information so later conversations become more personalized and require less repetition.
Save the key findings, evidence sources, hypotheses to verify, and related profiles from this research into long-term memory, then review them and fill gaps when I continue next time.
The tool preserves structured memory from the research process, helping restore progress quickly and continue analysis later.
Provide shared memory for Claude across apps with sessions, handoffs, and artifacts.
Manage persistent agent memories across global or repository-specific scopes.
Connect local memory vaults to MCP for persistent AI context read and write.
Persist Claude Code conversations and retrieve relevant context across sessions.
Help MCP clients remember preferences and retrieve key context across chats.
Manage personal memory, profiles, notes, and semantic search in one place.