Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Description from the maker (original English)
Generate and edit images with Google Gemini (Nano Banana / Nano Banana Pro) image models.
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
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_CARDValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"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"
}
}
}
}Run this in your terminal
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-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"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"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"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"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
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 envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account chrischall, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: GEMINI_API_KEY
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (2.5.1) reached the registry today.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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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