Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
제작자가 쓴 설명(영어 원문)
Generate and edit images with Google Gemini (Nano Banana / Nano Banana Pro) image models.
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.
GEMINI_API_KEY, GEMINI_IMAGE_MODEL, GEMINI_OUTPUT_DIR, GEMINI_INPUT_DIR, GEMINI_UPLOAD_DIR, GEMINI_REFERENCE_DIR, GEMINI_TIMEOUT_MS, GEMINI_HEARTBEAT_MS, GEMINI_CHAIN_RETRY_MS, GEMINI_DEBUG, GEMINI_RATE_CARD비밀로 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.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"gemini": {
"command": "npx",
"args": [
"-y",
"@chrischall/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your-value",
"GEMINI_IMAGE_MODEL": "your-value",
"GEMINI_OUTPUT_DIR": "your-value",
"GEMINI_INPUT_DIR": "your-value",
"GEMINI_UPLOAD_DIR": "your-value",
"GEMINI_REFERENCE_DIR": "your-value",
"GEMINI_TIMEOUT_MS": "your-value",
"GEMINI_HEARTBEAT_MS": "your-value",
"GEMINI_CHAIN_RETRY_MS": "your-value",
"GEMINI_DEBUG": "your-value",
"GEMINI_RATE_CARD": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add gemini --env GEMINI_API_KEY=your-value --env GEMINI_IMAGE_MODEL=your-value --env GEMINI_OUTPUT_DIR=your-value --env GEMINI_INPUT_DIR=your-value --env GEMINI_UPLOAD_DIR=your-value --env GEMINI_REFERENCE_DIR=your-value --env GEMINI_TIMEOUT_MS=your-value --env GEMINI_HEARTBEAT_MS=your-value --env GEMINI_CHAIN_RETRY_MS=your-value --env GEMINI_DEBUG=your-value --env GEMINI_RATE_CARD=your-value -- npx -y @chrischall/gemini-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"gemini": {
"command": "npx",
"args": [
"-y",
"@chrischall/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your-value",
"GEMINI_IMAGE_MODEL": "your-value",
"GEMINI_OUTPUT_DIR": "your-value",
"GEMINI_INPUT_DIR": "your-value",
"GEMINI_UPLOAD_DIR": "your-value",
"GEMINI_REFERENCE_DIR": "your-value",
"GEMINI_TIMEOUT_MS": "your-value",
"GEMINI_HEARTBEAT_MS": "your-value",
"GEMINI_CHAIN_RETRY_MS": "your-value",
"GEMINI_DEBUG": "your-value",
"GEMINI_RATE_CARD": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"gemini": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@chrischall/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your-value",
"GEMINI_IMAGE_MODEL": "your-value",
"GEMINI_OUTPUT_DIR": "your-value",
"GEMINI_INPUT_DIR": "your-value",
"GEMINI_UPLOAD_DIR": "your-value",
"GEMINI_REFERENCE_DIR": "your-value",
"GEMINI_TIMEOUT_MS": "your-value",
"GEMINI_HEARTBEAT_MS": "your-value",
"GEMINI_CHAIN_RETRY_MS": "your-value",
"GEMINI_DEBUG": "your-value",
"GEMINI_RATE_CARD": "your-value"
}
}
}
}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.
GEMINI_IMAGE_MODEL envGEMINI_OUTPUT_DIR envGEMINI_INPUT_DIR envGEMINI_UPLOAD_DIR envGEMINI_REFERENCE_DIR envGEMINI_TIMEOUT_MS envGEMINI_HEARTBEAT_MS envGEMINI_CHAIN_RETRY_MS envGEMINI_DEBUG envGEMINI_RATE_CARD env이 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 chrischall 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.
입력해야 할 값: GEMINI_API_KEY
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(2.5.0)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: Figma Context MCP, Claude Real Video, Figma MCP Server
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
MCP server for Google Gemini media generation. Exposes thirteen tools to Claude over stdio: list available models, generate/edit/compose images, generate a consistent set of images from a master prompt, multi-turn image refinement (Interactions API), video generation (omni), music generation (Lyria), an async result poll for long generations, and Files API upload/list/delete for reusable image references. Output is written to disk by default (path returned) or returned inline as base64. Built on the Gemini v1beta API (generativelanguage.googleapis.com) using the Nano Banana / Nano Banana Pro (images), omni (video), and Lyria (music) model families.
Developed and maintained by AI (Claude Code).
| Variable | Required | Description |
|---|---|---|
GEMINI_API_KEY | Yes | Your Google Gemini API key (aistudio.google.com/apikey) |
GEMINI_IMAGE_MODEL | No | Override the default image model (default: gemini-nano-banana-2.1) |
GEMINI_OUTPUT_DIR | No | Default directory for generated images (default: ~/Downloads/gemini-mcp). When set, a per-call output_dir must be inside it. |
GEMINI_INPUT_DIR | No | Directory to resolve bare input-image filenames against (so images: ["foo.jpg"] works) |
GEMINI_UPLOAD_DIR | No | Restrict local files streamed to the Gemini Files API (gemini_upload_file path, video_path) to these directories — one or more, separated by : (; on Windows); ~ allowed. A path outside is refused before any upload. Unset: no restriction |
GEMINI_REFERENCE_DIR | No | Restrict local reference images (the images / master_images paths read and sent to Gemini — inline, or as a Files API upload once reused) to these directories — :-separated (; on Windows), ~ allowed; GEMINI_OUTPUT_DIR is always allowed too, so generated images can be fed back in. A path outside (symlinks followed) is refused before it is read. Unset: GEMINI_UPLOAD_DIR applies instead. If both are unset, reference images are unrestricted on a local install (any file the server can read can be sent), and confined to $MCP_DATA_DIR/uploads when MCP_DATA_DIR is set (hosted) |
GEMINI_TIMEOUT_MS | No | Upstream request timeout in ms (default: 60000, or 120000 for image_size: "4K"); each generation tool also takes a per-call timeout_ms |
GEMINI_HEARTBEAT_MS | No | Progress-notification cadence in ms while a generation runs (default: 10000; 0 disables) — keeps MCP hosts that reset their timeout on progress from timing out long generations |
GEMINI_CHAIN_RETRY_MS | No | How long to wait out interactions-store lag when a chained call 404s (default: 120000; 0 disables retrying) |
Sending a local file to Google (the images / master_images / video_path inputs, or gemini_upload_file's path) and every delete ask for confirmation first. A client that can show a confirmation prompt (Claude Code) gets the real prompt, unless MCP_CONFIRM_ELICITATION=off. Elsewhere the first call does nothing and returns a preview (the resolved local paths with their MIME types and sizes, or the method/path being deleted) plus a confirmToken; only a repeat call with the same arguments and that token proceeds. The token is single-use, expires, and is bound to the exact arguments — a changed prompt or a swapped file between the two calls is refused. Pure text prompts, URLs, files/ references and base64 inputs are not gated.
| variable | default | |
|---|---|---|
MCP_CONFIRM_MODE | ask-user | What a write does on a client that cannot show a confirmation prompt (claude.ai, Claude Desktop). ask-user: two steps — the first call does nothing and returns a preview plus a token, and the model must get your approval in chat before calling again with it. auto: the same two steps, but the model may use the token after reviewing the preview itself. refuse: writes are refused on such clients. A client that can show prompts (Claude Code) always gets the real prompt, unless MCP_CONFIRM_ELICITATION=off. An unrecognised value is treated as refuse. |
MCP_CONFIRM_ELICITATION | on | off never shows a confirmation prompt, so every client gets the MCP_CONFIRM_MODE path. Set it for a client that claims to support prompts but never shows one (the gated call hangs — opencode 2.0.x). Any other value stays on, with a warning on stderr. |
MCP_CONFIRM_TTL_SECONDS | 600 | How long a token stays valid. |
MCP_CONFIRM_SECRET | random per process | Signing key; set it only if tokens must survive a server restart. |
4K / Pro-model generations can outrun an MCP host's own tools/call timeout (error -32001). The server sends notifications/progress heartbeats so hosts that reset their timeout on progress wait it out. If the host still gives up, the server-side generation usually completes anyway: the image is written to the output dir, gemini_interact also writes an .json sidecar recording the interaction_id, and continue_last: true resumes the interaction the lost response belonged to.
A 404 on a request carrying previous_interaction_id is not proof the chain expired. The only 404 body observed live is generic — "Requested entity was not found." — and never names *which* entity. An unknown or renamed model id, and an expired Files API `files/…` uri (~48h TTL), return exactly the same thing. So the server no longer asserts a cause it can't establish: the upstream text is surfaced verbatim, and gemini_interact runs an experiment to find out which it was.
Most often the id isn't missing at all — it just isn't *visible* yet. The interactions store is eventually consistent, and a freshly created id can 404 while the same id resolves fine minutes later; heavy turns (4K, Pro, thinking_level: high) are the likeliest to hit it, which is exactly the turn you most want to chain from. So a chained 404 is retried with exponential backoff for up to 120s (GEMINI_CHAIN_RETRY_MS) before anything is declared broken. The 404 generates nothing and isn't billed, so the wait costs only time.
After that budget is spent, the tool looks up that id's sidecar, re-attaches the image it produced, and re-issues the request without the chain:
chain_recovered: { expired_interaction_id, reanchored_on }. The 404'd attempt generates nothing, so this costs the one generation you'd have paid for re-anchoring manually.files/… uri instead of being sent to chase an interaction that was fine all along.Separately, continue_last no longer dies with the server process: with no in-memory id it resumes from the newest .json sidecar in the output dir and reports continued_from_sidecar: true. That case was never an expired chain at all — the interaction was alive upstream the whole time; only our memory of its id was gone.
For hosts whose timeout can't be tamed (e.g. Claude Desktop, a fixed ~30s cap that ignores progress), two guards make re-issuing safe and unnecessary:
job_id immediately instead of the image, so the call can't time out at all; poll gemini_get_result with the job_id until it's done.reused: true) instead of billing a second generation. (Even without a key, two identical in-flight calls are deduplicated automatically.)| Tool | Description |
|---|---|
gemini_list_models | List available Gemini image models and the current default |
gemini_image_generate | Generate image(s) from a text prompt |
gemini_image_edit | One-off edits or multi-image composition with a text instruction (for a series of edits, use gemini_interact) |
gemini_image_set | Generate a master image plus N consistent images referencing it |
gemini_interact | Preferred tool for iterative refinement: multi-turn generation/editing via the Interactions API — chain the returned interaction_id via previous_interaction_id (or continue_last: true) |
gemini_video_generate | Generate a short video (text→video, image→video, two-still interpolation, edit or extend) via the Gemini omni model; resolution 360p/720p/1080p/4k is the cost lever; written to disk as MP4 |
gemini_music_generate | Generate music from a text prompt via a Lyria model — lyria-3-clip-preview (30s, default), lyria-3.5 (full-length, vocals) or lyria-3-pro-preview; single-turn; written to disk as MP3 |
gemini_get_result | Fetch an async generation started with async: true by its job_id (status running → done result). Lets a long generation outlive a host's tools/call timeout |
gemini_token_usage | Token usage and an estimated USD cost for this session so far. Call it before and after a workflow and subtract to attribute that workflow's spend. Priced per call against each call's own model from a dated rate card (GEMINI_RATE_CARD overrides it); there is no account-balance endpoint to read, so this is how spend is attributed |
gemini_upload_file | Upload an image (or video/audio) to the Gemini Files API once — from a url, data_base64, or a local path — and get a reusable files/ reference |
gemini_list_files | List the files currently uploaded under this API key, with MIME types and expiry times |
gemini_delete_file | Delete an uploaded file before its ~48h expiry (confirmed first — see Confirmations) |
gemini_sign_media | *(hosted deployments only)* Mint a fresh signed URL for generated media from its r2_key — an expired link is not a dead end |
gemini_view_media | *(hosted deployments only)* Return a generated image as an inline image block from its r2_key, so a model can actually see what it made before refining it |
gemini_get_upload_url | *(hosted deployments only)* Mint a short-lived signed PUT URL so a shell can upload a reference image with no auth header; the PUT returns an r2_key usable in images_r2_keys, gemini_save_character, or gemini_upload_file |
gemini_save_character / gemini_list_characters / gemini_delete_character | *(hosted deployments only)* Persistent per-account character library: save a reference image + description under a name, then pass characters: ["name"] on generation tools. No expiry |
gemini_save_style / gemini_list_styles / gemini_delete_style | *(hosted deployments only)* Persistent per-account style presets: a reusable prompt fragment (optionally with a reference image), applied by passing style: "name" on generation tools. No expiry |
Generation tools also share three throughput/latency controls: async: true (return a job_id immediately), max_wait_ms (wait up to a budget, then hand back the job_id — fast results stay in-band, slow batches never trip the host timeout), and idempotency_key (a retry returns the recorded result instead of re-billing). On a hosted deployment, a gemini_image_set result with more than one image also carries a `bundle_url` — one sig
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