Video Caption MCP Server
An MCP server that automatically transcribes video content and burns stylized captions directly into the video file. It leverages the Groq Whisper API for fast transcription and supports multiple visual styles tailored for social media and professional content.
README
š¬ Video Caption MCP Server
An MCP (Model Context Protocol) server that automatically transcribes and burns stylized captions into videos. Designed to work with Poke by Interaction Co.
Upload a video ā AI transcribes it ā Stylized captions are burned in ā Download the result.
How It Works
You ā Poke: "Caption this video: https://example.com/video.mp4"
ā
Poke calls your MCP server's `caption_video` tool
ā
1. Downloads the video
2. FFmpeg extracts audio (16kHz mono WAV)
3. Groq Whisper API transcribes with timestamps (FREE!)
4. Generates SRT subtitle file
5. FFmpeg burns styled captions into the video
ā
Returns: download link + full transcript
Caption Styles
| Style | Look | Best For |
|---|---|---|
tiktok (default) |
Poppins bold white on dark box | TikTok, Reels, Shorts |
modern |
Poppins white with outline | General purpose |
classic |
Yellow text, bottom | Movies, TV style |
minimal |
Small Poppins, bottom-left | Clean, professional |
bold |
Impact font, heavy shadow | Maximum readability |
Setup (15 minutes)
1. Get a Free Groq API Key
- Go to console.groq.com
- Sign up (no credit card needed)
- Go to API Keys ā Create new key
- Copy the key ā you'll need it in step 3
Groq's free tier includes Whisper transcription at no cost with generous rate limits.
2. Deploy to Render
Option A: One-Click Deploy
- Click the button above
- Connect your GitHub account
- It will create a new repo from this template and deploy it
Option B: Manual Deploy
- Fork this repo to your GitHub
- Go to render.com ā New ā Web Service
- Connect your forked repo
- Render auto-detects the Dockerfile
- Click "Create Web Service"
3. Set Environment Variables
In your Render dashboard ā Environment:
| Variable | Value | Required |
|---|---|---|
GROQ_API_KEY |
Your Groq API key | ā Yes |
BASE_URL |
https://your-app-name.onrender.com |
ā Yes |
WHISPER_MODEL |
whisper-large-v3-turbo |
No (default) |
MAX_VIDEO_DURATION_SEC |
600 |
No (default: 10 min) |
PORT |
8000 |
No (default) |
ā ļø Important: Set
BASE_URLto your actual Render URL so download links work!
4. Connect to Poke
- Go to poke.com/settings/connections/integrations/new
- Enter a name:
Video Captioner - Enter the MCP Server URL:
https://your-app-name.onrender.com/mcp - Click Create Integration
5. Test It!
Message Poke:
"Use the Video Captioner integration's caption_video tool to caption this video: https://example.com/my-video.mp4"
Or more naturally:
"Can you add captions to this video? https://example.com/my-video.mp4 Use the bold style."
MCP Tools
caption_video
Transcribes and burns captions into a video.
Parameters:
video_url(required): Direct URL to a video filelanguage(optional): ISO-639-1 code, default"en"style(optional):modern,classic,minimal, orboldfont_size(optional): 12-72, default24
list_caption_styles
Returns all available caption style presets with descriptions.
Local Development
# Clone the repo
git clone https://github.com/YOUR_USERNAME/video-caption-mcp.git
cd video-caption-mcp
# Create virtual environment
python -m venv .venv
source .venv/bin/activate # or .venv\Scripts\activate on Windows
# Install dependencies
pip install -r requirements.txt
# Make sure FFmpeg is installed
ffmpeg -version # should work
# Set environment variables
export GROQ_API_KEY="your-key-here"
export BASE_URL="http://localhost:8000"
# Run the server
python src/server.py
Test with the MCP Inspector:
npx @modelcontextprotocol/inspector
# Connect to http://localhost:8000/mcp using "Streamable HTTP" transport
Architecture
video-caption-mcp/
āāā src/
ā āāā server.py # FastMCP server + file serving
āāā Dockerfile # Python 3.13 + FFmpeg
āāā render.yaml # Render deployment config
āāā requirements.txt # Python dependencies
āāā README.md
The server exposes:
POST /mcpā MCP protocol endpoint (for Poke)GET /files/{job_id}/{filename}ā Serves captioned video downloadsGET /healthā Health check
Limitations
- Video size: Groq free tier accepts audio up to 25 MB (roughly 10-15 min of video audio)
- Duration: Default max 10 minutes (configurable via
MAX_VIDEO_DURATION_SEC) - Render free tier: May spin down after inactivity; first request after sleep takes ~30s
- File cleanup: Output files are auto-deleted after 1 hour
- Direct URLs only: The video URL must be a direct download link (not YouTube, etc.)
Tips
- For YouTube/social media videos, use a service to get a direct download link first
- The
modernstyle works best for vertical/short-form video - Use
languageparameter for non-English videos for better accuracy - Groq's Whisper is extremely fast ā transcription usually takes just seconds
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.