# Orthanc DICOM

> Use this tool when you need to access and manage medical imaging data from Orthanc DICOM servers, enabling efficient querying and retrieval of patient studies, series, and DICOM objects. It solves problems in radiology automation workflows by providing hierarchical querying and PDF text extraction from DICOM reports. With inputs such as patient name, ID, or birth date, it outputs relevant imaging data and reports, ideal for use in healthcare and medical research contexts.

Canonical page: https://skillsregistry.net/skills/adiking117-orthanc-dicom  
JSON: https://api.skillsregistry.net/v1/skills/adiking117-orthanc-dicom

## Description

Connects to Orthanc DICOM servers to enable hierarchical querying of medical imaging data. Supports searching for patients by name, ID, or birth date, retrieving imaging studies, accessing series within studies, and querying individual DICOM objects. Includes PDF text extraction from encapsulated DICOM reports for radiology automation workflows.

## 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/adiking117-orthanc-dicom)
- **Repository:** <https://github.com/adiking117/orthanc-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": "adiking117-orthanc-dicom"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/adiking117-orthanc-dicom` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/adiking117-orthanc-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