Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Who calls this, what breaks, which callers an edit missed: labelled answers. Windows, Python, TS/JS.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"llmgraph": {
"command": "npx",
"args": [
"-y",
"llmgraph-mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add llmgraph -- npx -y llmgraph-mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"llmgraph": {
"command": "npx",
"args": [
"-y",
"llmgraph-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"llmgraph": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"llmgraph-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント brainfoods-studio で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.4.7)がレジストリに届いたのは昨日です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, Claude Checkpoint MCP
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
MCP server that checkpoints Claude Code session context to survive crashes and token limits
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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.
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.
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.
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.
| Label | What it means |
|---|---|
certain | We can prove it is exactly one function. |
exactly_these | A known set, and every member really can run here. |
within_these | One of a known list; some listed may never happen here. |
maybe_more | There are candidates, but the door is open. |
cannot_see | Nothing to go on. |
Answers carry no numbers about chance; they say what is ruled out.
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.
| Tool | What it answers |
|---|---|
who_calls | Every place that calls this function, plus calls we can't see. |
what_breaks_if_changed | Everything that depends on this, directly or indirectly, and what we can't see. |
check_my_changes | Manual check of edits: callers you didn't update, and anything we can't see. |
what_is_unknown | Where our view is blind (dynamic calls, unknown types, unreadable files) and why. |
explain | Why 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.
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