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Sipcode

作者:Anuj7411版本 1.7.1i★ –i在你的电脑上运行
注册名称io.github.Anuj7411/sipcode

安装

概览

作者提供的说明(英文原文)

Context hygiene for Claude Code: drift detection, re-read dedup, and token analytics.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 营销与社交媒体

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "sipcode": {
      "command": "npx",
      "args": [
        "-y",
        "sipcode",
        "sipcode-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add sipcode -- npx -y sipcode sipcode-mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "sipcode": {
      "command": "npx",
      "args": [
        "-y",
        "sipcode",
        "sipcode-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "sipcode": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "sipcode",
        "sipcode-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 Anuj7411 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“营销与社交媒体”中的其他服务器比较i

  • 星标数多于此分类中其他 2956 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2956 个服务器的 54% 更新
  • 基础检查结果等于或优于此分类中其他 2956 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Sipcode 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.7.1)于25天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

MCP YouTube Transcript

作者:jkawamoto

An MCP server retrieving transcripts of YouTube videos

在你的电脑上运行★ 495MIT9天前更新
安装

Google Analytics MCP

作者:surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

在你的电脑上运行★ 244MIT9天前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Sipcode

Keep Claude Code's context clean for sharper answers and lower cost, automatically.

Website · Compare · Releases


Install in 30 seconds

npm i -g sipcode

sipcode init

That is it. Your next Claude Code session will use Sipcode automatically. Verify a few minutes later:

sipcode drift

If the output reads no drift, context health stable, Sipcode is doing its job.

Already installed? Keep it fresh. Sipcode makes zero network calls, so it can't pop an "update available" notice. Build a weekly habit: run sipcode update (or npm i -g sipcode@latest) to pull the latest fixes. Full details in Updating Sipcode.


What is Sipcode?

Sipcode is a free command-line tool that sits between you and Claude Code. It does three things:

  1. It watches Claude Code's context window and warns you when it starts to bloat (we call this "context rot")
  2. It catches duplicate file reads and other waste before they reach Claude, so you pay less for the same answers
  3. It gives you receipts. Every saving is measurable in your terminal.

It is open source under the MIT license. It makes zero network calls during normal use. Your data never leaves your laptop.


How Sipcode compares

SipcodeTool ATool BTool C
ApproachLive PreToolUse hookCross-session memory storeStatic methodologyRAG retrieval server
Caps verbose tool output✓✗docs only✗
Dedups same-session re-reads✓✗docs only✗
Mid-session install support✓ Verified Warm-Filln/an/an/a
Zero false-dedup by construction✓n/an/an/a
Reproducible benchmark on locked corpus✓ 62.6% median (20 synthetic tasks)✗✗✗
Self-introspection MCP tools✓ 16 tools✗✗partial
Agents coveredClaude Code (all features); OpenAI Codex (spend analytics and usage limits, no hook)not comparednot comparednot compared
Zero network calls in normal use✓✓n/a✗
MIT licensed✓✓✓✓

Sipcode is complementary to memory tools that persist context across sessions (Tool A in the table). Sipcode keeps each individual session clean. They solve different problems. Run both for maximum effect.

Full feature-by-feature comparison with tool names revealed: anuj7411.github.io/sipcode/compare


Why you probably want it

If you use Claude Code for real work, you have already felt this:

  • Long sessions get expensive fast. A two-hour session on Claude Max can burn through your daily plan
  • Quality drops as the context window fills. Claude starts re-reading files, repeating itself, losing the thread of what you asked
  • You cannot tell what is bloat and what is signal

Sipcode measures the bloat, then removes the parts Claude does not need. Run sipcode benchmark on any machine and you will see the same 62.6% median reduction on the locked 20-task corpus. That corpus is synthetic: scripted pairs of Claude Code transcripts (without and with Sipcode), not recordings of live sessions. It shows what Sipcode's mechanisms remove from a modeled session. Your own number depends on your workload, and sipcode impact measures it on your real sessions.


The two-minute tour

After installing, here are the five commands that show you what Sipcode is doing.

1. sipcode drift

Tells you if your current Claude Code session is drifting from your normal usage pattern. Bloated context, repeated reads, stale signals are all flagged here.

✓ Sipcode drift: no drift, context health stable vs your recent baseline.

By default it checks your most recent session, across Claude Code and Codex. --session checks a specific one, --here limits it to sessions from the folder you are in, and --agent claude-code or --agent codex picks the tool.

2. sipcode proxy --stats

Shows what Sipcode caught in the current session, broken down by rewriter.

Sipcode proxy, rewrite stats

total rewrites: 144 est. tokens saved: ~288,685 (heuristic) signal kept: 67% (med), weighted across all rewrites

3. sipcode benchmark

Runs the locked 20-task corpus and produces a reproducible savings number. Anyone, anywhere can run this and get 62.6%. The transcripts are scripted, not recorded from live sessions, so read it as a model of Sipcode's mechanisms rather than a measured bill (see METHODOLOGY).

62.6%  median savings on a locked 20-task corpus

range 37.4% to 80.6% 3,567,170 tokens $22.48

4. sipcode today

Daily spend summary. Tokens used, sessions, output ratio, comparison to your 30-day median.

spend so far    $1.20    across 4 sessions

tokens so far 943.8K output ratio 3.7%

5. sipcode forecast

Month-end projection based on your last 14 days.

projected month-end   $17,674   (range $14,139 to $21,208)

Codex

Sipcode also reads OpenAI Codex CLI session logs (~/.codex/sessions and ~/.codex/archived_sessions, or the folder CODEX_HOME points to). For Codex this is spend analytics and usage limits: Sipcode reports what your Codex sessions used, where the tokens went, and how close you are to your plan's limits. It does not change what Codex does.

Commands that read Codex: stats, today, forecast, trend, impact, why, receipt, drift, regress and limits (Codex only), plus the session tools in the MCP server (they take an optional agent input: "claude-code" or "codex") and get_codex_limits.

  • --agent codex shows Codex only. --agent claude-code shows Claude Code only.
  • With no --agent flag and both tools installed, stats, today, forecast, trend and impact print one section per tool. stats, today and forecast end with one combined line, in this shape:
  Both tools: <total tokens> tokens · ~$<Claude Code> + ~$<Codex>
  • why, receipt and drift report on the most recent session across both tools. When the other tool has a recent session too, a one-line hint names it and the flag that shows it.
  • --here works for Codex too: it matches the working folder Codex recorded for each session.
  • --json covers one tool per call. Without --agent it covers Claude Code and prints a note on stderr when Codex logs exist too. Add --agent codex for Codex JSON.
  • With no --agent flag on a machine with Cursor and Codex, Sipcode shows Codex (it does not read Cursor's session logs).

How Codex tokens are counted. Sipcode reads Codex's per-request usage records, or, in logs from older Codex versions, the change in the running total Codex logs after each request. Cached input is part of Codex's input count, so Sipcode never bills cached tokens twice. A request copied into a resumed or forked session file is counted once. On the maintainer's machine, Sipcode's per-file totals equal Codex's own final total_token_usage on all 15 real session logs, and an independent counter that shares no code with Sipcode (scripts/verify-counts.mjs) cross-checks every period command against the same logs.

Prices. Codex models are priced from OpenAI's API price table (developers.openai.com/api/docs/pricing, and each Codex model's page under developers.openai.com/api/docs/models, as of 2026-10-09), including the long-context rate for prompts over 272,000 input tokens. A model with no known price is shown as unpriced: its tokens are still counted, a line under the cost says how many were left out of it, and it is never shown as $0.

Not supported for Codex yet: writing rules to AGENTS.md (rules, and the rules step of init), registering the MCP server in Codex, the proxy and hooks (proxy, hygiene), estimate and benchmark. rules --agent codex and estimate --agent codex stop with error E009 instead of showing Claude Code data.

Compressed Codex logs. Codex compresses older session logs to .jsonl.zst. Sipcode reads them exactly like plain logs on Node.js 22.15 or newer. On an older Node.js it skips them, and every report starts with a warning that says how many it could not read and that reading them needs Node.js 22.15 or newer. A damaged or unreadable log gets the same kind of warning. With --json the warning is a note on stderr and the JSON is unchanged.

Codex limits: sipcode limits

Codex writes your plan's usage-limit readings into its own logs after each request. sipcode limits reads them, with zero network calls, and answers three questions: when will I hit my limit, what used it, and did it shrink.

Example output of sipcode limits --since all (the tokens-per-1% history here goes back further than the default 90 days):

sipcode limits · Codex · plan: go · as of 2h ago (your last Codex request)

Weekly limit 62% used resets Wed 14 Oct 14:00 at this pace: runs out Tue 13 Oct ~18:00 30-day limit 22% used resets Mon 2 Nov at this pace: lasts until reset

What used your weekly limit (since Wed 7 Oct) 0199a1b2-c3d4-7a11 sipcode 31% 3.1M tokens 0199a0f7-11aa-7b02 my-app 17% 1.4M tokens codex-auto-review (9 requests) 6% unattributed (no Codex requests on this computer) 8%

Tokens per 1% of your weekly limit (gpt-5.4) Mar 28: 425K Apr 1: 357K Apr 13: 77K Possible limit cut around Apr 13: 5.1x fewer tokens per 1%. Limits cover your whole account. Codex use on other devices or in the cloud is not in these logs and can look like a cut.

  • Every limit window the logs report (5-hour, weekly, 30-day): percent used, reset time, and when it runs out at this pace. The pace is the percent used divided by the time since the period started, counted up to now, so the estimate moves later while you are not using Codex. "as of" is your last Codex request: the percent is only as fresh as that.
  • What used it: the current period's top 5 sessions and projects (folder name only), plus Codex's automatic reviews as one line. Each rise in the percent is shared by the requests made since the previous rise, in proportion to their tokens. A rise with no request on this computer shows as unattributed, because limits are shared with your other devices and Codex cloud.
  • Did it shrink: how many tokens 1% of the limit bought in each finished period with at least 20% used, compared only within one model (a period counts when 90% or more of its tokens came from one model). Periods that started

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