# DICOM

> Use this tool when you need to access and analyze medical imaging metadata, such as patient information and study details, from DICOM servers. It solves problems related to querying and extracting data from medical imaging systems, providing outputs in a readable format for AI assistants. The tool takes DICOM networking protocols as input and returns extracted metadata, making it ideal for medical professionals and researchers working within AI assistant conversations.

Canonical page: https://skillsregistry.net/skills/christianhinge-dicom  
JSON: https://api.skillsregistry.net/v1/skills/christianhinge-dicom

## Description

DICOM MCP Server enables AI assistants to interact with medical imaging systems through standard DICOM networking protocols. It provides tools for querying patient information, studies, series, and instances from DICOM servers, as well as extracting text from encapsulated PDF documents stored in DICOM format. Built on pynetdicom, the server supports multiple DICOM nodes, configurable calling AE titles, and various attribute presets for different query levels, making it particularly valuable for medical professionals and researchers who need to access and analyze medical imaging metadata without leaving their AI assistant conversation.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/christianhinge-dicom)
- **Repository:** <https://github.com/christianhinge/dicom-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "christianhinge-dicom"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/christianhinge-dicom` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/christianhinge-dicom/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt