This is proof of concept on how to use MCP to interactively benchmark vLLM.
We are not new to benchmarking, read our blog:
Benchmarking vLLM
This is just an exploration of possibilities with MCP.
Usage
- Clone the repository
- Add it to your MCP servers:
{
"mcpServers": {
"mcp-vllm": {
"command": "uv",
"args": [
"run",
"/Path/TO/mcp-vllm-benchmarking-tool/server.py"
]
}
}
}
Then you can prompt for example like this:
Do a vllm benchmark for this endpoint: http://10.0.101.39:8888
benchmark the following model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
run the benchmark 3 times with each 32 num prompts, then compare the results, but ignore the first iteration as that is just a warmup.
Todo:
- Due to some random outputs by vllm it may show that it found some invalid json. I have not really looked into it yet.