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DINO-X MCP Server

Official

Official MCP server powered by DINO-X for fine-grained object detection and image understanding.

GitHub source repository ↗

★ 109 Stars Category · Other Popular Source revision 83be2e9f02b1

54FMRS · D

Reliability

8/20

Security and permissions

10/20

Maintenance

11/20

Documentation

13/20

Setup experience

12/20

DINO-X MCP Server is a feature-rich, officially maintained object detection server offering multiple tools and flexible deployment options. It is suitable for developers to quickly integrate vision capabilities, but attention must be paid to API key security and data privacy.

Read the FMRS scoring method →

DINO-X MCP Server is the official Model Context Protocol (MCP) server that empowers LLMs with real-world visual perception through image object detection, localization, and captioning APIs. It leverages the DINO-X and Grounding DINO models to provide fine-grained object detection and image understanding for multimodal applications. The server supports STDIO and Streamable HTTP transport modes and offers tools for full-scene object detection, text-prompted object detection, human pose estimation, and visualization.

Tools

detect-all-objects

Detect all objects in the image, outputting categories, bounding boxes, and optional captions.

detect-objects-by-text

Detect objects based on English noun prompts, supporting dot-separated multiple categories, outputting bounding boxes and optional captions.

detect-human-pose-keypoints

Estimate human pose keypoints in the image, outputting 17 keypoints and bounding box, with optional captions.

visualize-detection-result

Visualize detection results by drawing on the image and saving the annotated image locally (STDIO only).

Setup

Ensure Node.js is installed (LTS recommended).
Get an API key from the DINO-X platform.
Choose a configuration method:

- Official hosted Streamable HTTP: Add the URL to your MCP client config, e.g., https://mcp.deepdataspace.com/mcp?key=your-api-key.
- Local npm package (STDIO): Configure your MCP client with the npx command and set the DINOX_API_KEY environment variable.
- Run from source: Clone the repository, install dependencies, build, and run with node.

Fit and risk

Best for

Developers building multimodal AI applications that require object detection and image understanding.
Vision QA tasks requiring precise object localization and attribute reasoning.
Scenarios needing rapid deployment of local or cloud vision perception services.

Not for

Scenarios processing video streams (currently only static images are supported).
Offline operation (requires API key and network connectivity).
Users with strict privacy requirements who cannot send images to external APIs.

Required permissions

Requires access to remote APIs (sending images to the DINO-X cloud platform).
In STDIO mode, may require local filesystem write permissions to save annotated images.

Risks and side effects

API key leakage: keep your API key secure and avoid exposing it in public repositories.
Data privacy: images are sent to the DINO-X platform for processing; ensure compliance with your data policies.
Dependency on external service: the server relies on the DINO-X cloud platform; network outages or service disruptions may affect availability.

Troubleshooting

If connection fails, check the API key and network access to the DINO-X platform.
If images cannot be processed, ensure the image format is jpg, jpeg, webp, or png, and that the URL is valid.
If annotated images cannot be saved in STDIO mode, check the `IMAGE_STORAGE_DIRECTORY` environment variable and write permissions.
In HTTP mode, verify the port is not in use and check firewall settings.

Use cases

Detect and visualize fire areas in a forest image.

Count the number of cardboard boxes in a warehouse image.

Find all red cars in an image.

Identify the tallest person and describe their clothing.

Full-scene detection, such as finding the fruit with the highest vitamin C content.

Analyze yoga poses from images.

Supported clients

Supported clients have not been confirmed yet.

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