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

Madar

作者:mohanagy版本 0.40.0-beta.1i★ –i在你的电脑上运行
注册名称io.github.mohanagy/madar

安装

概览

作者提供的说明(英文原文)

Authenticated local evidence paths for JavaScript and TypeScript coding agents.

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: 其他

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": {
    "madar": {
      "command": "npx",
      "args": [
        "-y",
        "@lubab/madar",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add madar -- npx -y @lubab/madar 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": {
    "madar": {
      "command": "npx",
      "args": [
        "-y",
        "@lubab/madar",
        "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": {
    "madar": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@lubab/madar",
        "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 mohanagy 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“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32466 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32466 个服务器的 20% 更新
  • 基础检查结果等于或优于此分类中其他 32466 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

Madar 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(0.40.0-beta.1)于3个月前进入注册中心。

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:Spec Driven Development, Remote Desktop Commander, HotCodePush

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

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

HotCodePush

作者:hotcodepush-team

Manage over-the-air (OTA) updates for React Native, Expo, Capacitor and Cordova apps.

在云端运行今天更新
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。

Madar

Retrieve specific source code for your coding agent.

Madar builds a local repository graph for JavaScript and TypeScript function lookup by file and symbol. Agents can inspect returned source and request omitted lines.

Broad context discovery and workflow packs are experimental: they can omit necessary evidence and increase total tokens once follow-up reads are counted. Consistent whole-task accuracy and token savings have not been established. Use direct source reads when they are sufficient.

Try It in 60 Seconds

Install Madar with Node.js 20 or newer. For an experimental discovery preview, run it inside your repository:

npm install -g @lubab/madar

cd your-repository madar try "how does authentication work?"

madar try builds or reuses the local graph, prints an experimental source preview, and shows an optional agent-install command. It does not modify your source code.

For a concrete example, Madar's included password-reset workspace contains this path:

account-routes.ts

-> PasswordResetService.requestPasswordReset() -> userRepository.saveResetToken() -> enqueueResetEmailJob() -> sendPasswordResetEmail()

This is an example of a partial starting path. The agent must verify the conditions, dependencies, and failure paths needed for its answer.

Connect Your Agent

Choose the agent you use. For Claude Code:

madar claude install --profile strict

madar doctor madar status

The compact strict profile exposes context_pack and context_expand; full also includes them, while core exposes graph-navigation tools. After installing, run madar doctor and madar status.

When the file and function are known, use this MCP request:

{

"prompt": "Read these functions", "task": "explain", "targets": [{"file": "lib/util.js", "symbol": "join"}], "budget": 1500 }

Replace the example file and symbol with those in your repository. Targets select function source, not a complete workflow; inspect omissions and returned continuation handles. A direct source read remains appropriate.

Without exact targets, questions such as these use experimental discovery:

How does authentication work?

Why does this endpoint return 403? Where is the report generated? What breaks if I change this service? Add telemetry to this flow.

For MCP source lookup and recovery, use strict. Codex and OpenCode install it automatically; Aider installs prompt guidance without an MCP server.

AgentInstall command
Claude Codemadar claude install --profile strict
Codex CLImadar codex install
Cursormadar cursor install --profile strict
GitHub Copilotmadar copilot install --profile strict
Gemini CLImadar gemini install --profile strict
Aidermadar aider install
OpenCodemadar opencode install

Installer details are in the CLI and MCP reference. Step-by-step setup and smoke tests are in the agent quickstarts.

After upgrading Madar, rerun your agent's install command to refresh its managed profile. Older profiles may lack automatic refresh or Codex's longer startup window.

During automatic reconciliation, graph-backed calls return a retryable response. If continuing with Madar, retry after its suggested delay. Native source investigation remains available.

What Changes for the Agent

context_pack returns source locations, excerpts, omissions, freshness, and advisory coverage. Its compact source_evidence_v2 response has a serialized token budget, including metadata. A small packet does not establish a cheaper or more accurate investigation.

For exact lookup, use up to eight JavaScript or TypeScript targets, each with a workspace-relative file and case-sensitive symbol. Only explain mode is supported. Missing, ambiguous, excluded, or stale owners are refused. Targets select functions, not complete workflows; they do not infer calls.

To inspect a known call instead, add "callee":"scan" to its caller target. Madar checks the full current caller and returns a uniquely bound local implementation. Identifier and static dotted calls are supported; nested-closure calls and dynamic expressions are excluded. Unverified bindings are refused.

One oversized exact function request returns a budgeted first page; continuations retrieve remaining lines without repetition.

For omitted evidence:

  • Follow a node's source_expand_handle with context_expand in the same MCP session. Continue with each returned handle until the remaining whole source lines are delivered. Changed or newly excluded source invalidates the handle.
  • Use an expandable handle for related evidence. An optional exact symbol selects a verified function inside that handle's scope. Do not pass a symbol with a source-continuation handle.
  • If a page reports budget_insufficient, retry with a larger budget or request fewer targets. Minimum budget: 128 tokens; expansion defaults to 1500.

A snippet_ref points to shared source text; use the referring node's snippet_line_range for its excerpt. When line_number is omitted, use that range's start. Response paths may be workspace-relative.

Experimental discovery can include source-resolved dependencies and static graph relationships. source_dependencies reports verified calls and unresolved locations; selection_omitted reports exact matches omitted by the lookup limit. Unresolved details may use either a flat list or grouped calls, including repeated line_numbers. Counts can exceed the bounded examples shown. None of these establishes runtime execution or whole-task completeness.

Regenerate older graphs to include newly supported source forms. Root/workspace package.json objects up to 128 KiB and JavaScript/TypeScript files under lib/ are eligible under source policy. Exclude generated output with .madarignore. Other JSON configuration files are not source evidence.

How It Works

  1. Madar indexes source files, declarations, imports, calls, framework metadata, and selected documentation locally.
  2. Exact targets or experimental query matching select source evidence.
  3. Responses expose omissions and recovery handles. Installed MCP profiles refresh the graph after workspace changes.

The MCP response shape describes the response contract.

Use Madar Without MCP

The CLI can generate and inspect context without installing an agent integration:

madar generate .

madar summary madar pack "how does auth work?" --task explain --format text

By default, madar generate . combines SPI metadata with proven legacy semantics for JavaScript/TypeScript, and uses legacy fallback for other supported languages. Strict modes are in the CLI reference.

Legacy updates rebuild the current corpus when files change or disappear, refreshing incoming calls and imports from unchanged files. Parser caches can still be reused; unchanged graphs are reused after any required extractor-version upgrade.

Create a provider-ready prompt:

madar prompt "how does auth work?" --provider claude

Create a share-safe handoff for another coding tool:

madar handoff "add auth telemetry" --task implement --consumer copilot

See the getting-started tutorial for a sample workspace.

Where Madar Fits

Consider precise source lookup when you know the JavaScript or TypeScript file and function and need selected bodies with explicit omissions and continuations.

It helps less when the repository is small, one direct read is sufficient, source is stale, or the question depends on dynamic or live runtime behavior. Architecture, review, and impact discovery remain experimental.

Madar complements agents and IDE indexing. It is not a hosted knowledge base, runtime tracer, PR reviewer, or vulnerability scanner.

Local by Design

  • Privacy: Madar graph generation runs locally and does not require an API key. Your coding agent may still send prompts or selected file context to its own model provider, depending on that agent's configuration.
  • Sensitive files: ordinary security source code remains indexable, while private keys, .env*, credential stores, and known non-source secret material are excluded. This is a path policy, not a content-level secret scanner.
  • Freshness: installed MCP profiles use automatic refresh. Manual CLI users can regenerate with madar generate .; strict workflows can require --require-fresh-context or --require-fresh-graph.
  • Worktrees: run Madar and the agent from the same linked Git worktree. Each worktree receives isolated graph artifacts outside the checkout; reconnect the MCP server after switching worktrees.
  • Telemetry: Telemetry is disabled unless you explicitly enable it. Controls and the exact source-safe event schema are documented in telemetry.

Treat every local MCP install, hook, or agent profile as part of your local trust boundary. Read the MCP threat model.

Evidence and Limits

Madar publishes the prompts, answers, traces, and share-safe reports behind its benchmark statements. Two public experiment types answer different questions and should not be compared as if they were the same test.

Controlled v0.30 evidence

Six June TypeScript runtime-flow trials used a source checkout with task-specific proof profiles. In those controlled runs, Madar was invoked once per row and the recorded results showed:

  • 3.5x to 18.5x fewer tool calls
  • 2.2x to 15.6x less provider-reported input
  • 1.65x to 7.09x lower latency

Those receipts are real measurements of profile-assisted Madar. They demonstrate what the workflow can achieve when the correct task evidence is available. They are not evidence that an untuned npm installation will reproduce the same result for arbitrary questions, because the old prompts and checkout retrieval contained benchmark-specific obligations unavailable to normal package users.

v0.31 production-artifact validation

The July reruns removed that assistance and used the same isolated, unpacked @lubab/madar@0.31.0 package artifact. Four of six repositories recorded an agent-adoption failure: no attributable Madar MCP call occurred. The other two invoked Madar but failed strict prompt or answer gates. The correct result is zero valid performance comparisons, not six product losses. These reruns expose adoption and answer-completeness work; they neither confirm nor refute the earlier controlled efficiency measurements.

Read the benchmark suite and all dated receipts or the shorter claims and evidence map.

Current Release

Current version: 0.33.0.

See the 0.33.0 changelog.

Documentation

NeedStart here

| First run | [Getting started](https://github.com/mohanagy/madar/blob/main/docs/tutorial

只显示了开头部分;其余内容请在仓库中阅读

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