Instructions to use openbmb/MiniCPM4-MCP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use openbmb/MiniCPM4-MCP with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="openbmb/MiniCPM4-MCP", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("openbmb/MiniCPM4-MCP", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use openbmb/MiniCPM4-MCP with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "openbmb/MiniCPM4-MCP"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM4-MCP",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/openbmb/MiniCPM4-MCP

SGLang

How to use openbmb/MiniCPM4-MCP with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "openbmb/MiniCPM4-MCP" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM4-MCP",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "openbmb/MiniCPM4-MCP" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM4-MCP",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use openbmb/MiniCPM4-MCP with Docker Model Runner:
```
docker model run hf.co/openbmb/MiniCPM4-MCP
```

SmartDazi commited on Jun 10, 2025

Commit

6c35761

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1 Parent(s): 4a6cefe

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@@ -49,7 +49,7 @@ As of now, MiniCPM4-MCP supports the following:
 - Cross-tool-calling capability: It can perform single- or multi-step tool calls using different tools that complies with the MCP.
 ## Evaluation
-The detailed evaluation script can be found on the [GitHub](https://github.com/OpenBMB/MiniCPM/tree/minicpm-4/demo/minicpm4/MCP) page. The evaluation results are presented below.
 | MCP Server                  |          | gpt-4o             |              |          | qwen3             |              |      |      minicpm4         |              |
 |-----------------------|----------------|--------------|--------------|---------------|--------------|--------------|----------------|--------------|--------------|

 - Cross-tool-calling capability: It can perform single- or multi-step tool calls using different tools that complies with the MCP.
 ## Evaluation
+The detailed evaluation script can be found on the [GitHub](https://github.com/OpenBMB/MiniCPM/tree/main/demo/minicpm4/MCP) page. The evaluation results are presented below.
 | MCP Server                  |          | gpt-4o             |              |          | qwen3             |              |      |      minicpm4         |              |
 |-----------------------|----------------|--------------|--------------|---------------|--------------|--------------|----------------|--------------|--------------|