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)
39 AI tools: transcription, video description, image & video generation, TTS, music, OCR via deAPI
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Works in Claude on the web, desktop and mobile:
https://mcp.deapi.ai/mcpRun this in your terminal
claude mcp add --transport http deapi https://mcp.deapi.ai/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"deapi": {
"url": "https://mcp.deapi.ai/mcp"
}
}
}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": {
"deapi": {
"type": "http",
"url": "https://mcp.deapi.ai/mcp"
}
}
}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.
ChatGPT connects only to servers on the internet:
https://mcp.deapi.ai/mcpMenu names can differ slightly by plan and over time.
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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 6, 2026
The registry name was verified with the GitHub account deapi-ai, which owns the repo
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Responded in 816 ms (HTTP 401)
Declares OAuth sign-in, so your AI app can take you to log in
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It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (0.6.2) reached the registry yesterday.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
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.
Production-ready Model Context Protocol (MCP) server for the deAPI REST API. This server exposes all deAPI AI capabilities as MCP tools, enabling LLMs to perform audio transcription, image generation, OCR, video generation, text-to-speech, and more.
deAPI v2 — this server targets the deAPI v2 client API (OpenAI-aligned noun paths under
/api/v2/*). API v1 is not supported: the tools send v2 payloads only.
audio_transcription - Transcribe audio files to text using Whisper modelsaudio_transcription_price - Calculate transcription costtext_to_audio - Convert text to natural speech (TTS)text_to_audio_price - Calculate TTS costtext_to_music - Generate music from text description and lyricstext_to_music_price - Calculate music generation costaudio_url_transcription - Transcribe audio from URLs of completed Twitter Spacesaudio_url_transcription_price - Calculate Twitter Spaces transcription costvideo_file_transcription - Transcribe video files to textvideo_file_transcription_price - Calculate video file transcription costvideo_url_transcription - Transcribe videos from URLs (YouTube, Twitter/X, Twitch, Kick, TikTok)video_url_transcription_price - Calculate video URL transcription costtext_to_image - Generate images from text promptsimage_to_image - Transform images with text guidanceimage_to_text - Extract text from images (OCR)image_remove_background - Remove background from imagesimage_upscale - Upscale images to higher resolutiontext_to_image_price - Calculate image generation costimage_to_image_price - Calculate image transformation costimage_to_text_price - Calculate OCR costimage_remove_background_price - Calculate background removal costimage_upscale_price - Calculate upscaling costtext_to_video - Generate videos from text promptsimage_to_video - Animate static images into videosaudio_to_video - Generate video conditioned on audio contentvideo_description - Describe a video in text (from an uploaded file or a video URL)video_upscale - Upscale a video to higher resolutiontext_to_video_price - Calculate text-to-video costimage_to_video_price - Calculate image-to-video costaudio_to_video_price - Calculate audio-to-video costvideo_description_price - Calculate video description costvideo_upscale_price - Calculate video upscaling costtext_to_embedding - Generate text embeddings for semantic searchtext_to_embedding_price - Calculate embedding costprompt_booster - Enhance a prompt for any deAPI inference type using AI guides (synchronous, returns refined prompt directly)prompt_booster_price - Calculate prompt-enhancement costget_balance - Check account balanceget_available_models - List available AI models with specificationscheck_job_status - Query async job status by ID; with wait_seconds it waits for the job and returns the finished result in the original tool's shape. A failed job reports success: false with error_reason, error_code, retryable and refundedEvery generation tool accepts webhook_url (HTTPS) and an optional webhook_secret (32–255 chars). deAPI calls that URL when the job finishes, signed with X-DeAPI-Signature: sha256= . ")>; the tool still returns the result to the caller as usual.
Generation parameters such as width, height, steps, frames and fps default to the selected model's own values when left unset — each model has different limits, so there is no fixed default that works everywhere. The get_available_models output and every tool description list each model's accepted ranges. Set enhance_prompt: true on text_to_image/image_to_image to let deAPI rewrite the prompt; the result then includes prompt_boost with the prompt actually used.
For running the MCP server:
uv, pip, or conda for package managementFor a deAPI account:
git clone https://github.com/deapi-ai/mcp-server-deapi.git
cd mcp-server-deapi
Option A: Using `uv` (recommended - fastest)
uv pip install -e .
Option B: Using `pip`
pip install -e .
Option C: Using `conda`
# Create conda environment
conda create -n mcp-server-deapi python=3.11 conda activate mcp-server-deapi
pip install -e .
.env file for configuration:# Copy the example file
cp .env.example .env
The server can run in two modes:
Local Mode (for use with Claude Desktop on the same machine):
MCP_HOST=127.0.0.1 python -m deapi_mcp.server_remote
The server starts on http://localhost:8000. On loopback it may run without DEAPI_JWT_SECRET_KEY (it then signs OAuth tokens with a per-process key, so a restart logs clients out).
Remote Mode (for deployment to a remote server):
# A fixed signing key is required whenever the server binds beyond loopback
export DEAPI_JWT_SECRET_KEY=$(python -c "import secrets; print(secrets.token_urlsafe(32))") MCP_HOST=0.0.0.0 MCP_PORT=8000 python -m deapi_mcp.server_remote
See the Remote Deployment section for production deployment options.
Both Claude Desktop and Claude.ai support MCP connectors with built-in OAuth authentication.
Name: deAPI
Remote MCP server: https://your-server-domain:8000/mcp
▼ Advanced settings OAuth Client ID: deapi-mcp OAuth Client Secret: YOUR_DEAPI_TOKEN
For details on the OAuth flow, see AUTH.md.
Best for: Server running on the same machine, quick setup without OAuth.
Edit your Claude Desktop config file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json{
"mcpServers": { "deapi": { "url": "http://localhost:8000/mcp", "headers": { "Authorization": "Bearer YOUR_DEAPI_TOKEN" } } } }
Replace YOUR_DEAPI_TOKEN with your actual deAPI token. Save the file and restart Claude Desktop.
Authentication is handled at the connection level, not per-tool-call. Tools do NOT accept a deapi_api_token parameter.
Here's an example workflow:
Use get_available_models to see available models
Use get_balance to check remaining credits
Use text_to_image with:
Use audio_transcription with:
Note: When calling tools via Claude Desktop or MCP SDK, authentication is handled automatically through the server connection (OAuth or HTTP headers). See AUTH.md for detailed OAuth setup.
deapi_mcp/deapi_client.py): HTTP client with auth forwarding, built on the deAPI Python SDK transportdeapi_mcp/polling_manager.py): Smart adaptive polling for async jobsdeapi_mcp/schemas.py): Pydantic models for type safetydeapi_mcp/auth_code_store.py): single-use OAuth authorization codes, in Redis when DEAPI_REDIS_HOST is set (so any replica can finish a login), otherwise in process memorydeapi_mcp/webhooks.py): optional HMAC-verified receiver for deAPI completion callbacks, so waiting tools wake on the callback instead of polling (DEAPI_WEBHOOKS_INTERNAL)deapi_mcp/tools/): Organized tool implementationsaudio.py - Audio transcription, TTS & music generation toolsimage.py - Image generation, transformation, OCR, background removal & upscalingvideo.py - Video generation, image/audio-to-video, description & upscale toolsembedding.py - Text embedding toolsprompt.py - Prompt booster toolsutility.py - Balance, models, status toolsThe server uses job-type-specific polling strategies:
| Job Type | Initial Delay | Max Delay | Timeout |
|---|---|---|---|
| Audio | 1s | 5s | 5 min |
| Image | 2s | 8s | 5 min |
| Video | 5s | 30s | 15 min |
| Embedding | 0.5s | 3s | 2 min |
Other (incl. check_job_status) | 2s | 10s | 5 min |
Polling uses exponential backoff with a configurable multiplier (default: 1.5x, DEAPI_POLLING_ __BACKOFF_FACTOR).
DEAPI_TOOL_MAX_WAIT (45 s, below the 60 s call timeout many MCP clients use). A job still running then returns success: true, done: false with its job_id, and check_job_status(job_id, wait_seconds=...) resumes the waitConfiguration can be set via environment variables (prefixed with DEAPI_). A variable set to an empty value (DEAPI_REDIS_PORT=) counts as unset and takes the default. Comments go on their own line: some tools (docker --env-file, kubectl create configmap --from-env-file) keep text after a value, # ... included, as part of that value. .env.example lists every variable with its default; the block below shows the common ones.
# API Configuration
DEAPI_API_BASE_URL=https://api.deapi.ai DEAPI_API_VERSION=v2
DEAPI_HTTP_TIMEOUT=30.0 DEAPI_MAX_RETRIES=3
DEAPI_TOOL_MAX_WAIT=45.0
DEAPI_POLLING
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