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Provide local-first governed AI memory with human approval and optional sync.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "@conxt/mcp" yet — see the docs or source repo.
Design a memory workflow for my AI agent: the agent proposes memories, a human reviews them before saving, and storage should be local-first.
A governed agent memory plan covering proposals, human approval, and local-first storage.
I want optional cloud sync for AI memory while keeping a local-first approach. Suggest an appropriate sync strategy and key considerations.
Implementation guidance on combining local-first memory with optional cloud sync.
Help me define approval rules for AI agent memory, including what kinds of memories should require human confirmation before saving.
A draft set of human approval rules for governed agent memory.
Developers building AI assistants or agents can use it to let agents propose memories first, then have humans decide whether to save them, reducing the risk of incorrect or inappropriate memories being stored directly.
When a team wants AI memory to stay primarily in the local environment, this MCP tool provides a local-first memory service suited to control-conscious workflows.
If memory needs to be synced across environments beyond local storage, optional cloud sync can be added on top of the existing governance flow without giving up human approval.
It is a local-first MCP server for governed AI memory. Agents propose memories to save, humans approve them before writing, and optional cloud sync can be enabled.
Yes, but the description says it is optional. The default emphasis is local-first, and details on whether and how to configure sync should be checked in the source repository.
The provided material only states that it is an MCP server and does not specify the runtime, installation steps, or key requirements. See the source repository for details.
Give AI assistants a persistent, searchable memory layer and context management.
Add persistent local semantic long-term memory to AI agents.
Give AI agents persistent memory and semantic retrieval across conversations.
Give AI agents persistent memory, searchable knowledge, and automatic consolidation.
Give AI assistants persistent memory with vector search, relationships, and access control.
Stores approved corrections and preferences so agents avoid repeating mistakes.