How do I give my AI agent persistent memory across machines and tools?
Use a remote memory service instead of copying local databases between machines. AI NetCafé's MCP server has built-in remember / recall / forget tools: memories stored with the same AllRouter key are shared across every machine and agent that uses that key — Claude Code on a laptop and Codex on a desktop recall the same decisions, preferences and verified fixes. Local capture tools like claude-mem pair well: capture locally, push only durable facts (decisions, bug fixes, discoveries) to the remote store. Nothing syncs to a third-party cloud you do not control.
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怎么让 Agent 拥有跨机器、跨工具的持久记忆?
别在机器之间复制本地数据库,用远端记忆服务。AI网吧的 MCP 自带 remember / recall / forget 三个工具:同一把 AllRouter Key 存的记忆,在所有机器、所有 Agent 之间共享——笔记本上的 Claude Code 和台式机上的 Codex 取到同一份决策、偏好与已验证修复。配合 claude-mem 这类本地捕获工具最佳:本地全量捕获,只把持久事实(决策/修复/发现)推到远端,不经过任何你控制不了的第三方云。
How to verify
Run the exact task through the tool below. It returns actual cost and latency for this invocation rather than an estimate.
Agent workflow
- Connect the MCP server (https://ainetcafe.com/mcp) with your AllRouter key in the Authorization header.
- During work, call remember for durable facts only: decisions, stable preferences, verified bug fixes, discoveries — never secrets or raw logs.
- On any other machine or agent with the same key, call recall (optionally with query and project) to restore context.
- Use forget(id) to delete anything wrong or sensitive.
Recommended tool: remember
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "remember",
"arguments": {
"content": "Decision: use SQLite FTS for v1 search, swap to vector search in v2.",
"kind": "decision",
"project": "my-app"
}
}
}MCP endpoint: https://ainetcafe.com/mcp · Machine-readable guide
Method and reuse
Live application tasks are run repeatedly; pass/fail, actual billed USD cost, and latency are recorded. Upstream-unavailable models are excluded from quality conclusions.
Data license: CC BY 4.0. Cite the page URL and measurement date.