Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Who calls this, what breaks, which callers an edit missed: labelled answers. Windows, Python, TS/JS.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"llmgraph": {
"command": "npx",
"args": [
"-y",
"llmgraph-mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add llmgraph -- npx -y llmgraph-mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"llmgraph": {
"command": "npx",
"args": [
"-y",
"llmgraph-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"llmgraph": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"llmgraph-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 brainfoods-studio 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.4.7)은 어제 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Zendesk
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
Zendesk MCP Pack — tickets, users, organizations via OAuth.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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