Netcafe Memory

com.ainetcafe由 ainetcafe.com 发布官方发布者v1.1.0更新于 Oct 27, 2026

Cross-session, cross-device memory for your agent: remember and recall notes. No key to start.

发布方自己的服务:Ai Netcafe

已验证Streamable HTTP可网页运行效率与工作流知识与记忆

概览

AI 生成的概览

托管式 MCP 端点,为智能体提供跨会话、跨设备的记忆:用 remember 存笔记,用 recall 取回。

可以做什么
  • 把笔记写入托管记忆库,按 AllRouter 密钥或匿名工作区令牌归属
  • 跨会话、跨设备取回此前保存的笔记
  • 同一端点还提供发票与对账单提取、SQL 方言转换、简历解析、定时任务等托管工具
  • 也可不装 MCP 客户端,直接用普通 HTTP GET 调用相同能力
适用场景
适合希望助手在不同对话之间或不同设备之间保留上下文、又不想自建存储的场景。若你想要一个免密钥的托管记忆服务,并愿意同时使用同一提供方的其他实用工具,也值得添加。
运行要求
远程 streamable HTTP 端点,位于 ainetcafe.com;无需安装包、密钥或环境变量即可开始。匿名调用有免费额度,可提供 AllRouter 密钥以继续使用。
安装前请注意
笔记会存放在第三方托管服务上,不要写入密钥或敏感个人数据。匿名使用绑定工作区令牌,超出免费额度后为付费使用;提供方称文档在内存中处理且不保留,但记忆笔记本身就是被持久保存的内容。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Netcafe Memory,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/com.ainetcafe%2Fnetcafe-memory/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "netcafe-memory": {
      "type": "http",
      "url": "https://ainetcafe.com/mcp/memory?s=registry"
    }
  }
}

README

ai-netcafe

[China: reachable]

Hosted tools your agent can call over MCP — and a claim you can check in one command:

bash
curl "https://ainetcafe.com/t/china_reachability?url=https://github.com"
json
{  "url": "https://github.com",  "tested_from": "mainland China (China Mobile backbone)",  "verdict": "unreachable: timeout (common signature of blocking or a very slow route)"}

That request was answered by a machine actually sitting on a Chinese backbone network. A monitor hosted anywhere else can only tell you GitHub is up where it is — which is not the question you were asking. That is the kind of thing we host: capabilities that are hard to get, rather than wrappers around ones that aren't.

Four focused servers

One agent profile rarely needs both spreadsheet cleanup and the Chinese lunar calendar, and every tool description costs tokens on every session. So the catalogue is served as four focused MCP endpoints — connect the one you need and pay the context cost of nothing else.

PackURLWhat it is
Tableshttps://ainetcafe.com/mcp/tableMessy CSV in, clean checkable table out. Dedupe, merge, transpose, wide→long, find what differs between two tables, reconcile two ledgers.
Dev kithttps://ainetcafe.com/mcp/devJSON↔YAML, validate JSON, line diff, regex test, JWT decode, SQL dialect transpile, timezone and unit conversion.
Doc flowhttps://ainetcafe.com/mcp/paperMarkdown → PDF / Word / PowerPoint / EPUB / HTML. PDFs merged, split, rotated, watermarked.
China factshttps://ainetcafe.com/mcp/cnMainland reachability from a real backbone, statutory holidays including make-up workdays (调休), offline ID and mobile validation, lunar calendar.

All four are in the official MCP registry as com.ainetcafe/netcafe-tables, -devkit, -docflow and -china.

Nothing in these four calls a language model or a third-party API. They compute on our own servers, so results are deterministic and repeatable — and they cannot break because someone else changed their API.

Numbers come with their own proof

Anything involving counts or money returns an arithmetic check computed in code, not asserted by a model:

jsonc
// reconcile_ledger: your books vs the bank statement{  "total_a": 105.30, "total_b": 106.80, "gap": -1.50,  "only_in_a":  [{ "key": "B",  "amount": 5.00 }],  "only_in_b":  [{ "key": "C",  "amount": 7.00 }],  "mismatched": [{ "key": "A3", "a": 100.00, "b": 99.50, "diff": 0.50 }],  "arithmetic_check": {    "formula": "A 105.3 − B 106.8 = -1.5; differences explain -1.5",    "checks_out": true  }}

If checks_out is false, the response says the result is untrustworthy instead of handing back a table that looks finished. Amounts are compared in integer cents, so 0.1 + 0.2 never invents a difference for someone to go chase.

Connect it

bash
claude mcp add --transport http netcafe-tables https://ainetcafe.com/mcp/table

DeepSeek Harness:

bash
dsh plugin --profile web add github:mario03690/dsh-netcafe

Everything is also a plain GET — no MCP client, no SDK, no key:

bash
curl "https://ainetcafe.com/t/cn_holiday?date=2026-10-01"curl "https://ainetcafe.com/t/diff_text?a=one%0Atwo&b=one%0Athree"

Charts come back as images you can paste straight into a README:

[live chart]

That image is rendered on request, right now, by the same service this page describes.

Model cost is measured, not quoted

bash
npx ai-netcafe compare "dedupe a JS array preserving order"
MODEL              COST       LATENCYdeepseek-v4-flash  $0.00012    7.6sgemini-3.5-flash   $0.000341   10.0sGLM5.2             $0.001828   9.0s
cheapest: deepseek-v4-flash   fastest: deepseek-v4-flash15.2× between cheapest and priciest

Every number is read from the upstream usage response, not derived from a published price list. That distinction matters more than it sounds — while building this we found the obvious conversion formula was wrong for several models (one off by ~9×, another by ~3×), and only billing-delta measurement matched reality. Full method and data.

Heavier skills

The main endpoint (https://ainetcafe.com/mcp) also carries tools that do call a model, and say so:

SkillWhat it does
extract_invoicesA batch of invoices → one ledger-ready table. Every row checked in code (net + tax = gross); the batch total re-added independently. Mixed currencies get no batch total on purpose — adding them would be an accounting error.
extract_statementBank statement PDF → transactions, with reconciliation (opening + credits − debits = closing). If it doesn't balance it says where the running total first breaks.
transpile_sqlSQL between dialects via a real parser, not a model — same input, same output, and syntax errors come back with line and column.
check_resumeWhether an ATS can actually parse a résumé. Rule-based and reproducible.
remember / recallCross-session memory, keyed to your AllRouter key or an anonymous workspace token.
create_taskHand a recurring job to a hosted runner; it notifies you only when the result actually changes.

Full catalogue: https://ainetcafe.com/tools?s=github

Backed by open-source projects — PDFMathTranslate, GPT Academic, GPT Researcher, NextChat, LobeChat — hosted pre-configured so you can try them without installing Docker, Python, or supplying a key.

CLI

bash
npx ai-netcafe compare "<prompt>"   # multi-model comparison with real costsnpx ai-netcafe ask "<prompt>"       # single modelnpx ai-netcafe apps                 # hosted apps + source reposnpx ai-netcafe models               # models with per-million pricesnpx ai-netcafe install              # MCP config for your agent

Quota

Anonymous calls get a free allowance — enough to try everything here, no signup. When it runs out the response tells you how to continue; nothing fails silently. Bring your own AllRouter key and token cost is billed to your own account at direct rates with no markup:

bash
export ALLROUTER_API_KEY=sk-...

Failed calls are not charged. Documents are processed in memory and not retained.

Links

Disclosure

Built and run by the people behind ainetcafe.com. It is our own service, with a free tier and paid usage beyond it. Links here carry an s= tag so we can tell which channel produces real usage — it identifies the channel, not you.

MIT

来源:README.md,提交 c14bb34

工具

0
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版本历史

1
  1. v1.1.0最新Sep 16, 2026

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