Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Madar

by mohanagyversion 0.40.0-beta.1i★ –iRuns on your computer
Registry nameio.github.mohanagy/madar

Install

Overview

Description from the maker (original English)

Authenticated local evidence paths for JavaScript and TypeScript coding agents.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

claude mcp add madar -- npx -y @lubab/madar mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account mohanagy, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32466 servers in this category
  • Published to the registry more recently than 20% of the other 32466 servers in this category
  • Basic checks equal to or better than 100% of the other 32466 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Madar safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.40.0-beta.1) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, HotCodePush

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

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

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

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

Runs in the cloud★ 211Updated yesterday
Install

HotCodePush

by hotcodepush-team

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

Runs in the cloudUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

Only the beginning is shown; read the rest in the repo

Ask PopNx