VisionAgent MCP Server

VisionAgent MCP Server is a lightweight, side‑car service that bridges Model Context Protocol (MCP) clients—such as Claude Desktop, Cursor, and Cline—with Landing AI’s VisionAgent REST APIs. By running locally on STDIN/STDOUT, the server translates each tool invocation from an AI assistant into a secure HTTPS request, then streams back structured JSON and media assets (images, masks) to the model. This eliminates the need for developers to write custom SDKs or REST wrappers, allowing natural‑language computer‑vision commands to be issued directly from their editor or IDE.

The server solves a common pain point for AI‑powered workflows: the friction of integrating external vision services into LLM agents. Developers can now issue high‑level prompts like “extract all tables from this PDF” or “detect every traffic light in the image” and receive fully parsed results without writing boilerplate code. VisionAgent MCP handles authentication, request formatting, response parsing, and media storage, providing a seamless plug‑in experience for any MCP‑compatible client.

Key capabilities include:

• Agentic Document Analysis – parses PDFs and images to extract text, tables, charts, and diagrams while respecting layout cues.
• Text‑to‑Object Detection – supports free‑form prompts such as “all traffic lights” using state‑of‑the‑art models (OWLv2, CountGD, Florence‑2).
• Text‑to‑Instance Segmentation – delivers pixel‑perfect masks via Florence‑2 combined with Segment‑Anything‑v2.
• Activity Recognition – identifies multiple activities in video streams, providing start and end timestamps.
• Depth Estimation (depth‑pro) – offers high‑resolution monocular depth maps for single images.

These features empower a variety of real‑world scenarios: automated invoice processing, dynamic image annotation for training datasets, surveillance video analysis, or any application that requires precise visual understanding without the overhead of building custom pipelines. By exposing a consistent MCP interface, VisionAgent MCP allows AI assistants to treat vision tasks as first‑class tools, dramatically accelerating development cycles and reducing integration complexity.