Marlin MCP

An MCP (Model Context Protocol) server that exposes NemoStation/Marlin-2B — a video language model — as tools for AI assistants. It provides two tools: describe_video (caption + scene + events) and search_video_event (temporal event grounding).

Repository: https://github.com/PromptEngineer48/Marlin-2B-MCP

Architecture

Claude / MCP Client
        │
        ▼  port 8006 (HTTP/MCP)
  marlin_mcp.py  ──────────────────► marlin_api.py  (port 8005)
                                           │
                                           ▼
                                     Marlin-2B (GPU)

marlin_api.py — FastAPI wrapper that loads the model and exposes /describe and /search endpoints on port 8005.
marlin_mcp.py — FastMCP server that wraps those endpoints as MCP tools, served on port 8006.

Setup

1. Update the system

apt-get update && apt-get upgrade -y

2. Install Miniconda

curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash ./Miniconda3-latest-Linux-x86_64.sh

Restart your shell or run source ~/.bashrc after installation.

3. Clone the repository

git clone https://github.com/PromptEngineer48/Marlin-2B-MCP.git
cd Marlin-2B-MCP

4. Create the conda environment

conda create -n vlm python=3.13 -y
conda activate vlm

5. Install MCP and requests

pip install mcp requests

6. Install the video model dependencies

pip install "transformers>=5.7.0" "torch>=2.11.0" torchcodec "qwen-vl-utils>=0.0.14" av pillow

7. Install torchvision (match your CUDA version)

Find the correct install command for your CUDA version at https://pytorch.org/ and run it. Example for CUDA 12.4:

pip install torchvision --index-url https://download.pytorch.org/whl/cu124

8. Install FastAPI and Uvicorn

pip install fastapi uvicorn

Running on RunPod

Before starting the servers, expose ports 8005 and 8006 in your RunPod pod settings under HTTP Ports.

RunPod will give you a public proxy URL for port 8006 in the format:

https://<pod-id>-8006.proxy.runpod.net/mcp

You will need this URL when configuring your MCP client.

Starting the servers

Terminal 1 — start the model API (port 8005)

conda activate vlm
uvicorn marlin_api:app --host 0.0.0.0 --port 8005

The first run downloads Marlin-2B (~5 GB). Wait for Marlin loaded. before proceeding.

Terminal 2 — start the MCP server (port 8006)

conda activate vlm
uvicorn marlin_mcp:app --host 0.0.0.0 --port 8006

Your MCP server is now live on port 8006.

MCP tools

| Tool | Description | |---|---| | describe_video(video_path) | Returns caption, scene, and events for a video file | | search_video_event(video_path, query) | Finds the timestamp span of a described event within the video |

Connecting to Hermes

Open your Hermes config file:

C:\Users\<your-username>\AppData\Local\hermes\config.yaml

Add the marlin entry under mcp_servers:

known_plugin_toolsets:
  mcp_servers:
    claude-code:
      command: claude
      args:
        - mcp
        - serve
      timeout: 300

    marlin:
      url: "https://<your-pod-id>-8006.proxy.runpod.net/mcp"
      timeout: 120
      connect_timeout: 60

Replace <your-pod-id> with the actual pod ID shown in your RunPod dashboard. The full URL is visible in RunPod under the pod's exposed HTTP ports.

Save the file and restart Hermes — the marlin toolset will appear and Marlin's video tools will be available.

MCP Servers