Senior LevelAI, LLMs, Embeddings & MCP
How do MCP Servers stream multi-gigabyte binary resources (videos, model weights) efficiently?
❓ Interview Prompt: Explain Model Context Protocol binary Blob resources, chunk-encoded Base64 streams, and presigned storage URLs.
Passing multi-gigabyte binary resources (such as video files or dataset archives) directly inside standard JSON-RPC text messages will crash MCP process memory buffers.
Efficient Binary Handling Strategies:
1
Presigned URL Handshake: The MCP server returns a temporary presigned cloud storage URL (
https://s3.amazonaws.com/...) inside the resource metadata response. The client downloads binary bytes out-of-band directly.2
Chunk-Encoded Base64 Streaming: For local Stdio connections, resources stream binary data in small Base64 chunks using
BlobResourceContents iteration.Code Implementation Example
typescript
// MCP Server exposing binary resource via Blob contents
server.setRequestHandler(ReadResourceRequestSchema, async (request) => {
if (request.params.uri === 'file:///media/video.mp4') {
const videoBuffer = await readChunkedFile(request.params.uri);
return {
contents: [{
uri: request.params.uri,
mimeType: 'video/mp4',
blob: videoBuffer.toString('base64') // Base64 blob block
}]
};
}
throw new Error('Resource not found');
});💡Exposing binary video file resource via MCP Base64 Blob contents.
🎯 Interview Key Takeaway
Stream large MCP binary resources using Base64 chunked blobs or out-of-band presigned storage URLs.
#MCP#Binary Resources#Streaming#Base64#Senior
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