프로토타입 · 미리 보기: 공식 레지스트리의 모든 서버를 담고 있으며 30분마다 동기화해요. 리뷰와 계정 기능은 다음 단계에서 열려요.
PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

ImageStep

제작자: imagestep버전 0.2.1i★ –i컴퓨터 또는 클라우드
레지스트리 이름dev.imagestep/mcp

설치

개요

제작자가 쓴 설명(영어 원문)

The image pipeline for agents: presets, assets and jobs. Answers with asset ids and stable URLs.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 컴퓨터 또는 클라우드
  • 전송 방식: stdio, Streamable HTTP
  • 카테고리: 디자인, 이미지 및 오디오
  • 입력해야 할 값: IMAGESTEP_API_KEY, Authorization

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 1개 통과
  • 제작자의 서버에서 실행돼요. 내가 요청한 내용은 제작자의 서버를 거쳐요.
  • 직접 입력할 값: IMAGESTEP_API_KEY, Authorization

비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.

필요한 것

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.

또는 내 컴퓨터에서 실행하기

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "mcpServers": {
    "imagestep": {
      "command": "npx",
      "args": [
        "-y",
        "@imagestep/mcp"
      ],
      "env": {
        "IMAGESTEP_API_KEY": "your-value"
      }
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add --transport http imagestep https://mcp.imagestep.dev/mcp --header 'Authorization: your-value'

또는 내 컴퓨터에서 실행하기

claude mcp add imagestep --env IMAGESTEP_API_KEY=your-value -- npx -y @imagestep/mcp

실행하기 전에 빈 값을 채워 주세요.

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "imagestep": {
      "url": "https://mcp.imagestep.dev/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

또는 내 컴퓨터에서 실행하기

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "imagestep": {
      "command": "npx",
      "args": [
        "-y",
        "@imagestep/mcp"
      ],
      "env": {
        "IMAGESTEP_API_KEY": "your-value"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "imagestep": {
      "type": "http",
      "url": "https://mcp.imagestep.dev/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

또는 내 컴퓨터에서 실행하기

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "imagestep": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@imagestep/mcp"
      ],
      "env": {
        "IMAGESTEP_API_KEY": "your-value"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

직접 입력할 값

  • IMAGESTEP_API_KEY 비밀 필수 env
    An ImageStep API key, created at https://imagestep.dev/keys?utm_source=mcp-registry&utm_medium=registry-entry
  • Authorization 비밀 필수 HTTP header
    Bearer followed by an ImageStep API key, created at https://imagestep.dev/keys?utm_source=mcp-registry&utm_medium=registry-entry

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 도메인 imagestep.dev 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    엔드포인트 응답

    아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요

  • … 아직 점검 안 함

    OAuth로 로그인

    아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요

디자인, 이미지 및 오디오 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 2179개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 2179개 중 74%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 2179개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

ImageStep, 안전한가요?

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.

어떤 키나 코드가 필요한가요?

입력해야 할 값: IMAGESTEP_API_KEY, Authorization

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

둘 다 가능해요. 내 컴퓨터에 설치해도 되고, 클라우드 버전에 연결해도 돼요.

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.2.1)은 11일 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Figma Context MCP, Claude Real Video, Figma MCP Server

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Figma Context MCP

제작자: GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

내 컴퓨터에서 실행★ 16,165MIT5개월 전 업데이트
설치

Claude Real Video

제작자: HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

내 컴퓨터에서 실행★ 2,284MIT2개월 전 업데이트
설치

Figma MCP Server

제작자: figma

The Figma MCP server brings Figma design context directly into your AI workflow.

클라우드에서 실행★ 2,15213개월 전 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

@imagestep/mcp

The image pipeline for agents: presets + assets + jobs, as MCP tools. Images never enter the context window — every tool takes and returns asset references (ids, sizes, public URLs).

ToolWhat it does
generateprompt → image(s); returns asset ids + CDN URLs. preset runs it through a saved preset whose subjects keep a character or product identical across a batch (slug@version to pin)
transformone atomic op — every op in GET /api/v1/ops but generate, read at startup (stdio) or per request (hosted), falling back to edit remove_bg upscale restore_face colorize analyze resize convert compress crop pad grayscale rotate flip flop trim flatten adjust mask blur_region overlay caption render_template read_metadata when the catalogue cannot be reached. render_template takes no images — parameters: {templateId, items}, one PNG per item. variants (≤ 20) runs the op once per variant in one job, every social size from one call. Two modes, chosen by the input — see below
run_presetrun a saved, versioned preset — a list of steps, by slug or slug@version (the way to chain ops and keep batches consistent)
job_statusper-item progress + outputs of a job (an analyze job answers with analyses). A write tool whose wait_seconds runs out returns the job handle with timedOut: true — not an error: the job keeps running and is charged for what completes, so poll this instead of submitting again. Read-only by default: pass publish: true to publish the outputs and get their public URLs. An answer carries at most 20 outputs (search_assets' page; past that outputsTruncated / outputsNote say to read on with search_assets {job_id, cursor}) — publish: true still publishes all of them. Items come a page at a time (the service's page): past the first, itemsCursor goes back as items_cursor for the next, and items_status (FAILED: what a resume would run again) reads only the items in one state; a chain item carries step / failedStep
search_assetsfind assets by collection, keyword, mime, size — or, with group_by: "collection", list your collections. One page per call; the answer's nextCursor, sent back as cursor, reads the next
save_presetsave a chain you will run again as a named, versioned preset — L1 op steps only, checked by the service before anything is stored; answers slug@version for run_preset to run pinned
send_feedbackreport what ImageStep could not do (capability_gap · bug · other) instead of working around it — free

Every tool declares an outputSchema: the keys it can answer with in structuredContent, all optional (which ones come back depends on the mode — a finished job, a wait that ran out, a dry run, a synchronous result, a refusal).

Inputs are asset_ids, urls (public http(s), fetched and ingested by the service — never downloaded by this server) or — when the server runs on your machine over stdio — file_paths. Every tool that spends money has dry_run (exact price, nothing created or uploaded — asset_ids are priced as themselves, file_paths / urls by how many) and returns structured errors with retryable, param and the service's requestId (quote it when reporting a failure), so a parameter mistake is refused before any credit is charged.

file_paths are files on your machine, and the agent naming them may be following an instruction it read in a page or a mail, so the server checks each one before reading a byte of it:

  • a path through a hidden file or folder — any name starting with . (~/.ssh, ~/.imagestep, .env) — is refused, also when a symlink leads there; ./ and ../ are resolved first;
  • when your client declares MCP roots, only files under them are read; when it declares none, IMAGESTEP_MCP_FILE_ROOTS (folders separated like PATH) does the same job; with neither, any other folder is readable;
  • roots are compared on real paths, so a symlink inside a root cannot lead out of it.

A refusal is invalid_param on file_paths and names the path by its index, never its contents. And a job over local files does not publish its outputs unless the call says publish: true — publish defaults to on only when the inputs are asset_ids or urls (and for generate).

The write tools (generate · transform · run_preset · save_preset · send_feedback) take an optional idempotency_key. An MCP client that times out makes the agent call the tool again; with the same key and the same arguments that second call returns what the first one answered — the job it created, the preset it saved — instead of submitting (and charging for) another. The same key with different arguments is refused with idempotency_key_reuse. Without a key, every call is a new submission.

Every tool carries MCP annotations, the hints a client reads to decide what needs your confirmation: job_status and search_assets are readOnlyHint; the write tools are not idempotent (without a key), and none is destructiveHint: every job writes new assets and never overwrites the one it read.

transform has two modes and the agent does not choose

Synchronous when all of these hold: exactly ONE local file or URL, a deterministic op, and wait: true. Nothing is stored in the account — no asset id exists afterwards, because none was created. Sub-second, and the account stays clean.

Where the result goes depends on which of the two servers you are talking to, because the two do not share a filesystem:

answerlifetime
stdio (this package on your machine)path — a temp file named for what the service says it produced (convert- .avif, not .bin)until the server exits; every result of one server lives in one temp directory
hosted (https://mcp.imagestep.dev/mcp)url — a signed link, plus expiresInSeconds~5 minutes; download it, or run the work as a job if you need a permanent URL

Both carry mimeType, width and height, so the next tool does not have to guess. The hosted answer is a URL for the obvious reason and it took a bug to notice it: your agent is not on the machine the server runs on, so a path into that container's /tmp is an answer it cannot read. Under the hood that is the API's own ?response=url, which writes the bytes to a short-lived temp object — still nothing in your asset catalogue.

As a job for everything else: several images, asset_ids, any AI op, or wait: false. You get asset ids and public URLs, plus progress, cancellation and webhooks.

Which ops may go the first way is read from GET /api/v1/ops (syncEndpoint), never hard-coded — a deterministic op added to the API is fast here without this package changing. If the catalogue cannot be reached, the job path is used: slower is a better failure than wrong.

A urls input is judged the same on both paths: it must resolve to a public address, and it is refused here — before anything leaves the process — not only by the service that would fetch it. One input never gets two answers because of which transport happened to carry it.

Neither mode ever returns image bytes. An image in the context window is tokens the agent pays for and cannot read; the answer is always a path, an id or a URL.

Resources

URIWhat it is
imagestep://opsGET /api/v1/ops as is — every op with its parameter contract (type, default, description), prompt and asset requirements, default model and pricing
imagestep://ops/{op}one op's entry (template; listed per op when the catalogue was readable at startup)
imagestep://models/{mode}GET /api/v1/ai-models?mode= — ai_image or analyze, with prices
imagestep://usageGET /api/v1/usage?groupBy=op — what the account spent over the last 30 days, per op
imagestep://agent-guidelinesthe operating contract (below)

The catalogue resources exist because an MCP-only client (Claude Desktop) cannot curl the API or open the console, and "never invent a parameter" is a rule it can only follow if it can read them. transform also carries a one-line-per-op summary — name(type=default), plus the values a parameter takes when the catalogue lists them, what a required one means, and for an AI op the model's own parameters object — generated from the same catalogue; when that could not be read, it falls back to a built-in summary and says so. All five are read live: a read that cannot reach the service fails rather than answering from a copy.

imagestep://agent-guidelines is the operating contract — read the op catalogue instead of carrying a list, price with a dry run before spending, branch on retryable rather than the status code, keep a batch consistent with a preset, and report a missing capability instead of working around it. It is a resource rather than a tool because a tool is something an agent decides to call and the rules are something it should have read, and it is fetched from the service on every read, so a copy of this package released months ago still serves today's contract.

Connect

Get an API key at https://imagestep.dev/keys?utm_source=npm&utm_medium=mcp-readme.

Claude Desktop (claude_desktop_config.json) — local, can upload files from disk:

{

"mcpServers": { "imagestep": { "command": "npx", "args": ["-y", "@imagestep/mcp"], "env": { "IMAGESTEP_API_KEY": "is_sk_…" } } } }

Cursor (.cursor/mcp.json) — same shape:

{ "mcpServers": { "imagestep": { "command": "npx", "args": ["-y", "@imagestep/mcp"], "env": { "IMAGESTEP_API_KEY": "is_sk_…" } } } }

Claude Code — local:

claude mcp add imagestep -e IMAGESTEP_API_KEY=is_sk_… -- npx -y @imagestep/mcp

Remote (any client that speaks Streamable HTTP) — nothing to install:

claude mcp add --transport http imagestep https://mcp.imagestep.dev/mcp --header "Authorization: Bearer is_sk_…"

The remote server is stateless: each request is served by a fresh server bound to the API key in the Authorization header (Bearer or ApiKey). file_paths is disabled there; pass urls or asset_ids. It logs one JSON line per request on stdout: the JSON-RPC method, the tool name of a tools/call, the clientInfo an initialize reports, your key's prefix (the 12 characters the console shows — never the key), whether the key is valid, the HTTP status and the duration. Never a tool's arguments or your prompt. The validity comes from a side request to the API (3 s timeout, not counted as a use of the key), and the answer, valid or not, stands for five minutes. The handshake never waits for it. A request that can call the API on your key (a tool call, a resource read) does, when the server has not seen that key yet, so a wrong key is turned down there with the same unauthorized error the API gives and never reaches the API. An address whose keys turned out invalid 20 times in a minute gets HTTP 429 with Retry-After for any key the server has not seen yet, until the minute is up; a key it already knows to be good keeps working.

The remote server waits at most 90 s per tool call (wait_seconds above that is clamped; the default there is 90). It answers each call as one JSON body, so nothing reaches your client until the tool returns, and Cloudflare's edge drops a response that has not started after 100 s — you would get an HTML 524 with no job id while the job kept running. Past 90 s you get the job handle with timedOut: true instead; poll job_status. Over stdio the wait is what you ask for (default 180 s, max 600 s).

Try it

Upload ./product.jpg, remove the background, upscale it 2×, and give me the URL.

The agent calls transform (remove_bg, file_paths), then transform (upscale, asset_ids = the previous output, `parameters:

앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요

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