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dpansumisra

VideoReceiverMCP

by dpansumisra
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Python
Hybrid

VideoReceiverMCP

A minimal MCP (Model Context Protocol) server that receives video files over both:

  • stdio — for local agents (Claude Desktop, Cursor)

  • HTTP (Streamable-HTTP) — for remote/network clients

How it works

Sender project                    VideoReceiverMCP server
     |                                      |
     | 1. encode video -> base64 string     |
     | 2. call receive_video(base64) -----> |
     |                                      | 3. decode base64 -> binary
     |                                      | 4. save to received_videos/
     | <-- "Video received! ..."            |

MCP uses JSON-RPC (text only), so videos are base64-encoded before sending.

Related MCP server: golpo-mcp

Setup (local)

# 1. Run the setup script (creates venv + installs deps)
.\setup.ps1

# 2. Activate venv
.\venv\Scripts\Activate.ps1

Run locally

stdio mode (for Claude Desktop / Cursor)

python video_mcp_server.py

HTTP mode (test network transport locally)

python video_mcp_server.py --http
# MCP endpoint: http://localhost:8000/mcp

Configure in Claude Desktop

Edit %APPDATA%\Claude\claude_desktop_config.json:

{
  "mcpServers": {
    "VideoReceiverMCP": {
      "command": "C:/path/to/mcp/venv/Scripts/python.exe",
      "args": ["C:/path/to/mcp/video_mcp_server.py"]
    }
  }
}

Configure in Cursor / VS Code

Edit .cursor/mcp.json in your project:

{
  "mcpServers": {
    "VideoReceiverMCP": {
      "command": "C:/path/to/mcp/venv/Scripts/python.exe",
      "args": ["C:/path/to/mcp/video_mcp_server.py"]
    }
  }
}

Deploy on Render (free, persistent server)

Why Render and not Netlify? Netlify runs serverless/stateless functions — they cannot keep a persistent connection open, which MCP Streamable-HTTP requires. Render's free tier runs a full persistent Python process.

  1. Push this repo to GitHub

  2. Go to render.com -> New -> Web Service

  3. Connect your GitHub repo — Render auto-reads render.yaml

  4. Deploy! Your MCP endpoint will be:

    https://<your-app>.onrender.com/mcp

Connect your other project to the deployed server

# In your other project:
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
import base64, asyncio

async def send_video(video_path: str, server_url: str):
    with open(video_path, "rb") as f:
        b64 = base64.b64encode(f.read()).decode()

    async with streamablehttp_client(server_url) as (read, write, _):
        async with ClientSession(read, write) as session:
            await session.initialize()
            result = await session.call_tool(
                "receive_video",
                arguments={"video_base64": b64, "filename": "clip.mp4"}
            )
            print(result.content[0].text)

asyncio.run(send_video("myvideo.mp4", "https://your-app.onrender.com/mcp"))

Available Tools

Tool

Args

Description

receive_video

video_base64, filename?, description?

Receives a base64 video, saves to received_videos/

list_received_videos

—

Lists all saved videos

delete_video

filename

Deletes a video from the server

Test with the included client

# stdio (local)
python send_video_client.py myvideo.mp4

# HTTP (local server running on port 8000)
python send_video_client.py myvideo.mp4 --url http://localhost:8000/mcp

# HTTP (deployed on Render)
python send_video_client.py myvideo.mp4 --url https://your-app.onrender.com/mcp

Limitations

Issue

Notes

Size overhead

Base64 adds ~33% to file size

Large files

Videos >50 MB may strain memory / context windows

Netlify

Cannot host persistent MCP HTTP servers — use Render instead

Project structure

mcp/
├── video_mcp_server.py     # MCP server (stdio + HTTP transport)
├── send_video_client.py    # Test client (stdio + HTTP)
├── requirements.txt        # Python dependencies
├── setup.ps1               # One-click setup script
├── render.yaml             # Render deployment config
├── Procfile                # Railway / Heroku deployment
├── .gitignore
├── received_videos/        # Videos saved here (auto-created)
├── video_proxy_mcp.py      # Local proxy MCP (VS Code / Antigravity IDE)
└── .vscode/mcp.json        # MCP server config for VS Code / Antigravity IDE

VS Code & Antigravity IDE Integration

The local proxy (video_proxy_mcp.py) bridges your AI IDE to the remote Render server.
It handles Base64 encoding automatically — just pass a plain file path.

Architecture (detailed)

┌─────────────────────────────────────────────────────────────┐
│              AI Agent (Antigravity IDE / GitHub Copilot)    │
│                  — asks to upload / download a video —      │
└─────────────────────┬───────────────────────────────────────┘
                      │  stdio  (JSON-RPC over stdin/stdout)
                      ▼
┌─────────────────────────────────────────────────────────────┐
│                  video_proxy_mcp.py  (LOCAL)                │
│                                                             │
│  upload_video(path, description)                            │
│    1. Path(path).read_bytes()   ← reads binary from disk    │
│    2. base64.b64encode(raw)     ← ~33 % size overhead       │
│    3. _call_remote("receive_video", {...})                  │
│                                                             │
│  download_video(filename, output_path)                      │
│    1. _call_remote("download_video", {...})                 │
│    2. base64.b64decode(response["video_base64"])            │
│    3. Path(output_path).write_bytes(raw)                    │
│                                                             │
│  list_videos()   → _call_remote("list_received_videos", {}) │
│  delete_video()  → _call_remote("delete_video", {...})      │
└─────────────────────┬───────────────────────────────────────┘
                      │  HTTPS  (Streamable-HTTP / JSON-RPC)
                      │  timeout: 300 s (large file support)
                      ▼
┌─────────────────────────────────────────────────────────────┐
│         https://mcp-rgi7.onrender.com/mcp  (REMOTE)         │
│                  video_mcp_server.py                        │
│                                                             │
│  receive_video(video_base64, filename, description)         │
│    1. base64.b64decode(video_base64) → raw bytes            │
│    2. open(received_videos/<filename>, "wb").write(raw)     │
│    3. returns status + file size                            │
│                                                             │
│  download_video(filename)                                   │
│    1. open(received_videos/<filename>, "rb").read()         │
│    2. returns JSON { filename, size_bytes, video_base64 }   │
│                                                             │
│  list_received_videos()  → scans received_videos/ on disk   │
│  delete_video(filename)  → os.remove(received_videos/…)     │
└─────────────────────┬───────────────────────────────────────┘
                      │
                      ▼
              /opt/render/project/src/
                  received_videos/
                    clip.mp4
                    demo.mp4
                    ...

Architecture (simplified overview — original)

AI Agent (VS Code / Antigravity IDE)
       │  stdio
       ▼
video_proxy_mcp.py  (runs locally)
       │
       ├─ reads file from disk
       ├─ Base64-encodes it
       └─ forwards to remote MCP
              │  HTTPS
              ▼
https://mcp-rgi7.onrender.com/mcp

Setup

The .vscode/mcp.json file is already in this repo. VS Code and Antigravity IDE both pick it up automatically on startup:

{
  "servers": {
    "video-proxy": {
      "command": "python",
      "args": ["d:/workspace/mcp/video_proxy_mcp.py"]
    }
  }
}

Available proxy tools

Tool

What to say to the agent

upload_video

"Upload D:\clips\demo.mp4 to the server"

download_video

"Download clip.mp4 to C:\Downloads\clip.mp4"

list_videos

"List all videos on the server"

delete_video

"Delete clip.mp4 from the server"

VS Code — uploading a video

VS Code upload demo alt text alt text After the upload completes, the server confirms the file name, size, and saved path:

VS Code upload result

Listing all videos stored on the server:

VS Code list videos

Antigravity IDE — uploading a video

Antigravity IDE upload demo Antigravity IDE list videos After the upload the server returns the same confirmation:

Antigravity IDE upload result

Note: The Render free tier sleeps after inactivity. The first request may take 30–60 seconds to wake the server up. Subsequent calls are fast.

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