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PopNx MCPMCP servers for people who use AI · explained in plain words

Llmgraph

by brainfoods-studioversion 0.4.7i★ –iRuns on your computer
Registry nameio.github.brainfoods-studio/llmgraph

Install

Overview

Description from the maker (original English)

Who calls this, what breaks, which callers an edit missed: labelled answers. Windows, Python, TS/JS.

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

Run this in your terminal

claude mcp add llmgraph -- npx -y llmgraph-mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "llmgraph": {
      "command": "npx",
      "args": [
        "-y",
        "llmgraph-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": {
    "llmgraph": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "llmgraph-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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account brainfoods-studio, 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 32696 servers in this category
  • Published to the registry more recently than 95% of the other 32696 servers in this category
  • Basic checks equal to or better than 100% of the other 32696 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 Llmgraph 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 (0.4.7) reached the registry yesterday.

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, LexPact UK Contracts

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

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Runs on your computer★ 440MITUpdated 14 months ago
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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 2 days ago
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Runs on your computerUpdated today
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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.

LLMGRAPH by Brainfoods Studio: the truth layer for coding agents

Every call graph has blind spots. Ours tells you where they are.

A local MCP server and Claude Code plugin that tells your coding agent who calls a function, what breaks if it changes, which callers an edit missed, and what it can't see. Windows x64; Python and TypeScript/JavaScript. Real answers, no sign-up: beta.llmgraph.in/docs/real-answers.

LLMGRAPH inks only the calls it can prove. The ones it can't see, it counts and names in plain words, so your agent sees the blind spots before it edits.

I built LLMGRAPH as the truth layer for coding agents, and the truth includes the blind spots: agents guess; LLMGRAPH proves what it can and names what it can't. In a blind test of 50 questions on three open-source repos, no confident answer was wrong.


Two functions. One name. Your agent can't tell. We can.

grep reads names. LLMGRAPH follows calls. What it can prove, it proves; what it can't, it tells you, down to the line where it stopped.

zod ships two copies of addIssueToContext. A text search mixes them together:

$ rg -n addIssueToContext      # zod v3.23.8

146 lines, from both copies, mixed together

LLMGRAPH separates them, and shows its work:

llmgraph · who_calls addIssueToContext (src/helpers/parseUtil.ts:72): 71 in a set

⚠︎ type checker starting: answers use our own reading for now; 71 calls unchecked ◇ within_these 71 calls -> one of 1 (closed: repo only) [c] w1 ⚠︎ plus 7 dynamic calls nearby that could reach anything w2 – ruled out: 71 same-name calls (proven: other target) [c] w3 assumes [c]: our own reading, not confirmed by the checker (lines trimmed)

71 look-alikes ruled out, and it shows why. And where the type checker hasn't confirmed yet, it says so.

Who's holding the other end?

Before your agent pulls a thread, it should know. In requests, change super_len(o) to super_len(o, strict), and ask check_my_changes:

llmgraph · check_my_changes: 1 file changed, 16 calls break

16 breaks: misses "strict" w1 ⚠︎ breaks if it runs super_len src/requests/models.py:526 PreparedRequest.prepare_body (within_these, one of 1, closed: repo only) [c] w2 ⚠︎ breaks if it runs super_len src/requests/models.py:575 PreparedRequest.prepare_content_length (within_these, one of 1, closed: repo only) [c] w3 ⚠︎ breaks if it runs super_len tests/test_utils.py:62 TestSuperLen.test_io_streams (within_these, one of 1, closed: repo only) [c] w4 … 13 more test call sites ⚠︎ plus 9 dynamic calls nearby that could reach super_len w18 (lines trimmed)

16 broken calls named, exactly the real ones. A blind tester's text search found the same 16, no more and no fewer. And the 9 dynamic calls it can't follow are marked, not ignored.

Then the type checker catches up. Ask again a few seconds later:

llmgraph · who_calls super_len (src/requests/utils.py:135): 16 certain

✓ certain src/requests/models.py:526 PreparedRequest.prepare_body w33 +1 more (all certain, same file) w34 ✓ certain tests/test_utils.py:62 TestSuperLen.test_io_streams w35 +13 more (all certain, same file) w36 ⚠ plus 9 dynamic calls nearby that could reach anything w37 (lines trimmed)

From "our own reading" to 16 `certain`, on the released program. Its labels never say more than it has proven, and they upgrade the moment it can.

The five labels

Other tools sketch your codebase from rumour and fill the blind spots with confidence. LLMGRAPH works in two colours: ink for what it has proven, a plain warning for what it hasn't, and never one dressed up as the other.

LabelWhat it means
certainWe can prove it is exactly one function.
exactly_theseA known set, and every member really can run here.
within_theseOne of a known list; some listed may never happen here.
maybe_moreThere are candidates, but the door is open.
cannot_seeNothing to go on.

Answers carry no numbers about chance; they say what is ruled out.

Measured on our test projects

Callers are confirmed by the type checker in under a second after your agent asks (Python), and check_my_changes answers in under a second once LLMGRAPH has caught up with a save. On names that also appear in unrelated code, it named no wrong callers where a plain text search returned hundreds of wrong lines, and the agent read less than half as many tokens; on clean, unique names there is no saving.

How we measured, the raw data, and where LLMGRAPH loses: BENCHMARKS.md.

See real answers, no sign-up needed: beta.llmgraph.in/docs/real-answers.

What your agent can ask

ToolWhat it answers
who_callsEvery place that calls this function, plus calls we can't see.
what_breaks_if_changedEverything that depends on this, directly or indirectly, and what we can't see.
check_my_changesManual check of edits: callers you didn't update, and anything we can't see.
what_is_unknownWhere our view is blind (dynamic calls, unknown types, unreadable files) and why.
explainWhy we said this: the evidence behind one answer line.

Your code is read and analysed on your machine, and we never receive your code, paths, symbol or repo names, queries or answers. Checked on the released program: it contacts only beta.llmgraph.in. Usage counts and crash reports are on by default and can be switched off (npx -y llmgraph-mcp telemetry off); the licence check is always on. Privacy page.

Install

Claude Code (plugin):

claude plugin marketplace add brainfoods-studio/llmgraph-agent-plugin

claude plugin install llmgraph@llmgraph

The plugin offers LLMGRAPH's answer before your agent searches for a function or class name, and never blocks the search. When your agent is about to finish, it stops it once if the saved edits left calls that are certain to break, and lists them; it never blocks on anything less, and npx -y llmgraph-mcp hook off turns both off.

Any MCP agent: add the server npx -y llmgraph-mcp (on Windows some agents need cmd /c npx -y llmgraph-mcp), sign in once with Google, and your agent asks. Setup guides for Claude Code, Antigravity, Cursor, Codex, Gemini CLI, Windsurf and OpenCode; tested by us on Claude Code and Antigravity.

Which project it reads: the first answer of each session names it (project: (from )). Without --repo it is the folder your agent names, else the folder the server started in. If that is not your project, reconnect llmgraph (in Claude Code, /mcp), or name the folder with --repo or LLMGRAPH_REPO in a project .mcp.json (the plugin's own entry names none, as it serves every project):

{

"mcpServers": { "llmgraph": { "command": "npx", "args": ["-y", "llmgraph-mcp", "--repo", "C:\\work\\my-project"] } } }

Today's limits: Windows x64 · Python and TypeScript/JavaScript (other languages are reported as cannot_see, not counted as nothing) · repos up to the plan's line limit · invite-only beta, request an invite · one plan for individuals with a trial, prices.

This repo holds the open setup files under MIT; the LLMGRAPH engine is closed source and runs on your machine under the EULA. Brainfoods Studio, India · founder@llmgraph.in · security@llmgraph.in

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