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PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

ImageStep

作者:imagestepバージョン 0.2.1i★ –iパソコンでもクラウドでも
レジストリ名dev.imagestep/mcp

インストール

概要

作者による説明(英語の原文)

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

PopNx MCPの3つの柱

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。

できること

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。

  • 接続方法: パソコンでもクラウドでも
  • トランスポート: stdio, Streamable HTTP
  • カテゴリ: デザイン・画像・音声
  • 入力が必要なもの:IMAGESTEP_API_KEY, Authorization

インストール

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。

インストールの前に

「秘密」と表示された値は、あなたのアカウントの鍵です。絶対に人に教えたり、チャットに貼り付けたりしないでください。

必要なもの

  • クラウドで動くインストール不要。インターネット経由でつながります
  • npmNode.jsのインストール(npxコマンドに必要)

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。

このアドレスはリクエストの header にキーが必要ですが、コネクタを追加するメニューでは設定できません。代わりにClaude Code、Cursor、VS Codeを使ってください。

または、パソコンで動かす

Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます

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

ターミナルでこれを実行します

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

または、パソコンで動かす

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

動かす前に、空欄の値を入力してください。

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

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

または、パソコンで動かす

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

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

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。

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

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

または、パソコンで動かす

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

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

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。

このアドレスはリクエストの header にキーが必要ですが、コネクタを追加するメニューでは設定できません。代わりにClaude Code、Cursor、VS Codeを使ってください。

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。

自分で入力する値

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

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。

できること

このサーバーのツール一覧はまだ読み取っていません。エンドポイントは順番にチェックしています。

基本チェックi

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6日にチェック

  • ✓ 合格

    作者とリポジトリが一致

    レジストリ名はドメイン imagestep.dev で確認済みです(レジストリがドメインの所有を確認しています)

  • … 未チェック

    今もメンテナンスされている

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    ライセンスがある

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    エンドポイントが応答する

    まだチェックしていません。エンドポイントは順番にチェックしています

  • … 未チェック

    OAuthでサインイン

    まだチェックしていません。エンドポイントは順番にチェックしています

  • … 未チェック

    ツールの説明に隠れた指示がない

    まだチェックしていません。エンドポイントをチェックするときにツール一覧を読み取ります

デザイン・画像・音声のほかのサーバーとの比較i

  • このカテゴリのほかの2180件のうち0%よりスターが多い
  • このカテゴリのほかの2180件のうち74%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの2180件のうち100%と同じかそれ以上

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。

よくある質問

ImageStepは安全ですか?

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。

どんなキーやコードが必要ですか?

入力が必要なもの:IMAGESTEP_API_KEY, Authorization

パソコンで動きますか、それともクラウドですか?

どちらでも使えます。パソコンにインストールしても、クラウド版につないでもかまいません。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は–、最新バージョン(0.2.1)がレジストリに届いたのは11 日前です。

どのアプリで使えますか?

Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。

代わりに使えるものは?

同じカテゴリには:Figma Context MCP, Claude Real Video, Figma MCP Server

代わりの候補

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

Figma Context MCP

作者:GLips

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

パソコンで動く★ 16,165MIT5 か月前更新
インストール

Claude Real Video

作者:HUANGCHIHHUNGLeo

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

パソコンで動く★ 2,284MIT2 か月前更新
インストール

Figma MCP Server

作者:figma

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

クラウドで動く★ 2,15213 か月前更新
インストール

作者のREADME

READMEを開く

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。

@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:

冒頭だけを表示しています。続きはリポジトリで読めます

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