原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

knock

作者:HasanGilani版本 0.2.0i★ –i在你的电脑上运行
注册名称io.github.HasanGilani/knock

安装

概览

作者提供的说明(英文原文)

Code map and memory for AI coding agents: key functions, line ranges, callers, why code changed.

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: 搜索与 AI 记忆

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

  • PyPI已安装 Python 的 uv(用于 uvx 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": {
    "knock": {
      "command": "uvx",
      "args": [
        "knock-mcp",
        "serve",
        "--repo",
        ".",
        "--toolset",
        "map"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add knock -- uvx knock-mcp serve --repo . --toolset map

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": {
    "knock": {
      "command": "uvx",
      "args": [
        "knock-mcp",
        "serve",
        "--repo",
        ".",
        "--toolset",
        "map"
      ]
    }
  }
}

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": {
    "knock": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "knock-mcp",
        "serve",
        "--repo",
        ".",
        "--toolset",
        "map"
      ]
    }
  }
}

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7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 HasanGilani 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“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7266 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7266 个服务器的 90% 更新
  • 基础检查结果等于或优于此分类中其他 7266 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

knock 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(0.2.0)于4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 Python (uv)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

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

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
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。

🚪 knock

Stop Claude Code from burning your usage limit on big repos.

On a large codebase, Claude Code spends much of each session searching and reading files, often through a sub-agent, before it answers you. knock gives it a map of the code up front: the functions that matter, their exact line ranges, and who calls what. It runs on your machine and needs no API key.

Same question, 8 runs each, on a 4,776-file repo: median cost $0.42 → $0.25 (−40%). Without knock, Claude spawned a sub-agent in 5 of 8 runs. With knock, in none.

claude mcp add knock -- uvx knock-mcp serve --repo . --toolset map

Full code map for Python and JavaScript/TypeScript; functions and classes for Go, Rust, Java and more.

Two real Claude Code sessions on Saleor , abridged: each side's median-cost run out of three. Results vary between runs and repositories; on a small, well-known repo the difference was within noise. Full numbers: docs/benchmark.md · how it was measured: the write-up .


🤔 The problem, in one table

Every new chat with a coding agent starts with amnesia. To answer *"where is X?"* or *"how do we deploy?"* it greps, opens big files, reads them... and next session it does it all over again.

😩 Without knock😎 With knock
First movegrep around, open whole files, or spawn a sub-agent to exploreone map call: the relevant code as a skeleton with exact line ranges
Text the agent reads~27,000–118,000 characters per question~4,300 characters per question
Finds "why did we do it this way?"only if it opens the right docdecisions and their rationale come back with the answer
Remembers yesterday's bug hunt❌✅ agents save findings with remember
Knows when its notes are outdated—✅ every answer says fresh or stale

Median characters per task on the held-out benchmark (targeted-grep and grep-and-read baselines vs knock). Fewer characters ≠ an identical cut in your bill; see the FAQ .

⚡ Getting started

You set knock up once, then you just keep using your AI agent as usual. The agent talks to knock in the background; you never have to run knock commands day to day.

1️⃣ Connect it to Claude Code (once per project)

From inside the project you work on:

claude mcp add knock -- uvx knock-mcp serve --repo . --toolset map

This uses uv, which downloads and runs knock for you. No uv? Run pipx install knock-mcp (or pip install knock-mcp), then claude mcp add knock -- knock serve --repo . --toolset map.

--toolset map gives the agent three tools (map, open, remember) and is the setup measured in the results below. Leave it out to get the original eight tools.

That's the whole setup. The next time you open Claude Code in that project, knock reads the project and builds its notes automatically. This takes a few seconds for a small project and a minute or two for about 5,000 files; after that it only re-reads files that changed.

[!TIP]

Add this line to your project's CLAUDE.md so the agent uses knock when it pays off:

*"Before exploring the repo (how/why questions, unclear bugs, changes across modules, code you can't find with one search), call knock's map tool with your task. For small edits you can locate with one grep, skip it. Save non-obvious findings with remember."*

In our recordings, knock saved money on investigations in a large codebase but added a small cost to quick edits, so this line matters.

2️⃣ Work normally

Ask your agent what you'd always ask. Here's what changes behind the scenes:

You typeWhat the agent does
*"Add rate limiting to the login endpoint"*asks knock first and gets the login handler's file:line, your middleware conventions and the test setup, then opens only those lines
*"Why do we use Postgres instead of Mongo?"*gets the decision and its reasoning from your docs or ADRs, with a link to the source
*"Tests fail with a Redis error, any idea?"*finds the finding a previous session saved: *"login tests need Redis running"*
*(after it figures something out)*saves it with remember, so tomorrow's session already knows

Nothing to maintain: when code changes, knock updates its notes, and flags anything that may be outdated.

🖥️ Optional: use knock yourself from the terminal

You never *need* these, but they're handy.

CommandWhen you'd use it
knock map "where are expired checkouts cleaned up?"see the same code map your agent gets
knock open SomeClass.methodexact code for a symbol, with its callers and callees
knock context "how do we deploy?"ask a question yourself, e.g. when onboarding onto an unfamiliar repo
knock search "rate limit"look up what knock knows about a topic
knock statuscheck how fresh the notes are and how much knock knows
knock index .update the notes right now; your agent normally does this for you
knock index . --fullrebuild everything from scratch after a huge refactor
knock forget . --yesdelete everything knock stored about this project

Want knock to ignore some files? List them in a .knockignore file (same format as .gitignore).

👥 Setting it up for a whole team

Commit a .mcp.json file to your repo, and every teammate's Claude Code picks up knock automatically (each person needs knock installed):

{

"mcpServers": { "knock": { "command": "knock", "args": ["serve", "--repo", ".", "--toolset", "map"] } } }

Each person's notes live on their own machine. Sharing findings across a team isn't supported yet (see Status below).

🧠 How it works

flowchart LR

A["📁 Your repo code · docs · configs · git log"] -->|"knock index (only changed files)"| B["🗂️ Notes each one points to file + lines + hash"] B --> C[("💾 SQLite on your machine")] C -->|"map"| D["🤖 Your agent"] D -->|"open / Read (verify the real lines)"| A D -->|"remember (save what it learned)"| C

  1. Index: knock reads your repo *without running anything in it*. It writes short notes: what each module defines, what the docs say about setup and deployment, which tools and dependencies you use, why decisions were made, and which recent commits fixed bugs.
  2. Ask: your agent asks a question and gets a small, ranked answer with file:line pointers, instead of reading whole files.
  3. Verify: before editing, the agent reads just the lines it needs. The original files are always the source of truth.
  4. Remember: the agent saves what it learned. If those files change later, knock marks the note stale so nobody trusts outdated info.

🧰 What your agent gets

With --toolset map (recommended):

ToolWhat it does
map🗺️Use when you'd otherwise explore. The code relevant to a task as a skeleton: signatures, exact line ranges, what each function uses and catches, who calls it; plus the history behind it and the docs that matter. For change requests, a lighter version with the exact range to read and existing code to copy.
open📄Exact, line-numbered code for a function or class with its callers and callees, a line range, or a file's skeleton
remember✍️Save a finding for future sessions; it's flagged automatically when the cited files change

The original 8-tool set (default without --toolset map )

ToolWhat it does
get_context🔎Start here when you'd otherwise explore. A ranked package for a task: notes, functions with file:line, files worth opening, related commits, and honest "nothing known about X" gaps
search_knowledge📚Search notes, filtered by category (architecture, decision, workflow, …) or folder
get_knowledge🧾One note with full provenance: where it came from, when, and whether it is still current
get_source📄Read real lines from a file, with secrets redacted. Only files knock indexed
record_knowledge✍️Save a finding; duplicates are merged, contradictions flagged
update_knowledge_status✅Mark a note verified, or wrong
get_repository_status🩺How fresh the index is, plus counts and stats
refresh_repository🔄Re-index changed files (takes milliseconds, no AI calls)

👀 See a real example session (8-tool set, Flask)

On Flask, an agent is told: *"sessions signed with an old key in SECRET_KEY_FALLBACKS are rejected after rotating SECRET_KEY"*.

  1. `get_context` returns ~7.7 KB containing:
  • src/flask/sessions.py:317: SecureCookieSessionInterface.get_signing_serializer
  • tests/test_basic.py:374: test_session_secret_key_fallbacks
  • related commits fb54159861 secret key rotation: fix key list ordering and e13373f838 enable secret key rotation
  • the docs sections on sessions and secret keys
  1. `get_source("src/flask/sessions.py", symbol="get_signing_serializer")` returns the ~80 relevant lines, not the whole file.
  2. `record_knowledge` saves the finding:
   {"category": "debugging",

"content": "get_signing_serializer builds the key list as SECRET_KEY_FALLBACKS followed by SECRET_KEY; ordering was fixed in fb54159.", "sources": [{"path": "src/flask/sessions.py", "start_line": 317, "end_line": 335}]}

   The next session gets it instantly. If `sessions.py` changes, the note is flagged **stale**.

📊 Does it actually help?

Measured with a reproducible benchmark: 12 engineering tasks per repo, covering architecture, finding a feature, deployment, bug investigation, design rationale and following conventions.

Held-out repo (full-stack-fastapi-template; knock was never tuned on it):

ApproachFound the needed factsCharacters readTool calls
🐢 grep + read 3 files9 / 121,215,57072
🐇 targeted grep + read snippets7 / 12328,20660
🚪 knock10 / 1288,96217

More numbers, and the fine print

  • Flask (used during development, so optimistic): knock 12/12 with 92K chars, baselines 7/12 with 2.1M and 247K chars.
  • Speed: a ~200-file repo indexes in 0.3–0.6 s; re-indexing with no changes takes ~30 ms.
  • What this measures: whether the facts

只显示了开头部分;其余内容请在仓库中阅读

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