Histopathology Annotation MCP server

Histopathology Annotation MCP

<!-- mcp-name: io.github.sachinbkale27/label-image-mcp -->

An MCP server for annotating histopathology and other images in Image Label, a free annotation tool. It lets Claude and other AI assistants upload images, outline every nucleus in an H&E slide automatically (StarDist), trace regions from rough boxes (Segment Anything, or MedSAM for medical images), check slide quality, normalize stain colours, clean up annotations, and export COCO, YOLO or QuPath GeoJSON. A LangGraph agent is included.

Try it in the browser: https://agent.sachin-kale.com/#annotate: upload a slide and annotate it, detect nuclei, check its quality or get an AI interpretation, with no setup.

Published as label-image-mcp (PyPI) and io.github.sachinbkale27/label-image-mcp (MCP Registry).

Use cases and setup guide: https://labels.sachin-kale.com/mcp

LangGraph agent (label-image-agent)      Claude Desktop / Claude Code / any MCP client
              │  langchain-mcp-adapters             │
              └──────────────┬──────────────────────┘
                             ▼
                    label-image-mcp (stdio or HTTP)
                             │
                             ▼
                 Image Label API  (/api/images ...)

Account

The tools need an Image Label account (request one). They see, change and upload only images saved to that account; without one they see no images. Work kept only in your browser is not visible to them.

Install

Claude Desktop: download label-image-mcp.mcpb from the latest release, open it, and enter your username and password when asked.

Claude Code:

claude mcp add label-image -e LABEL_USERNAME=... -e LABEL_PASSWORD=... -- uvx label-image-mcp

Any MCP client (needs uv):

{
  "mcpServers": {
    "label-image": {
      "command": "uvx",
      "args": ["label-image-mcp"],
      "env": { "LABEL_USERNAME": "...", "LABEL_PASSWORD": "..." }
    }
  }
}

Agent skill

skills/label-image/SKILL.md teaches the agent when and how to use these tools: which annotation types end up in exports, cleaning up labels safely, and merging per-image exports into one COCO or YOLO dataset with consistent class ids (bundled scripts/merge_exports.py). It follows the open SKILL.md format, so it works in Claude Code and other agents that support skills.

# Claude Code: install for all your projects (or copy into a project's .claude/skills/)
git clone --depth 1 https://github.com/sachinbkale27/label-image-mcp /tmp/label-image-mcp
mkdir -p ~/.claude/skills && cp -r /tmp/label-image-mcp/skills/label-image ~/.claude/skills/

Configuration

Tools

Shortened. The full README is on GitHub.