The dicom-mcp
server enables AI assistants to query, read, and move data on DICOM servers (PACS, VNA, etc.).
🤝 Contribute • 📝 Report Bug • 📝 Blog Post 1
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🧑⚕️ User: "Any significant findings in John Doe's previous CT report?"
🧠 LLM → ⚙️ Tools:
query_patients → query_studies → query_series → extract_pdf_text_from_dicom
💬 LLM Response: "The report from 2025-03-26 mentions a history of splenomegaly (enlarged spleen)"
🧑⚕️ User: "What's the volume of his spleen at the last scan and the scan today?"
🧠 LLM → ⚙️ Tools:
(query_studies → query_series → move_series → query_series → extract_pdf_text_from_dicom) x2
(The move_series tool sends the latest CT to a DICOM segmentation node, which returns volume PDF report)
💬 LLM Response: "last year 2024-03-26: 412cm³, today 2025-04-10: 350cm³"
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dicom-mcp
provides tools to:
- 🔍 Query Metadata: Search for patients, studies, series, and instances using various criteria.
- 📄 Read DICOM Reports (PDF): Retrieve DICOM instances containing encapsulated PDFs (e.g., clinical reports) and extract the text content.
- ➡️ Send DICOM Images: Send series or studies to other DICOM destinations, e.g. AI endpoints for image segmentation, classification, etc.
- ⚙️ Utilities: Manage connections and understand query options.
Install using uv or pip:
uv tool install dicom-mcp
Or by cloning the repository:
# Clone and set up development environment
git clone https://github.com/ChristianHinge/dicom-mcp
cd dicom mcp
# Create and activate virtual environment
uv venv
source .venv/bin/activate
# Install with test dependencies
uv pip install -e ".[dev]"
dicom-mcp
requires a YAML configuration file (config.yaml
or similar) defining DICOM nodes and calling AE titles. Adapt the configuration or keep as is for compatibility with the sample ORTHANC Server.
nodes:
main:
host: "localhost"
port: 4242
ae_title: "ORTHANC"
description: "Local Orthanc DICOM server"
current_node: "main"
calling_aet: "MCPSCU"
Warning
DICOM-MCP is not meant for clinical use, and should not be connected with live hospital databases or databases with patient-sensitive data. Doing so could lead to both loss of patient data, and leakage of patient data onto the internet. DICOM-MCP can be used with locally hosted open-weight LLMs for complete data privacy.
If you don't have a DICOM server available, you can run a local ORTHANC server using Docker:
Clone the repository and install test dependencies pip install -e ".[dev]
cd tests
docker ocmpose up -d
cd ..
pytest # uploads dummy pdf data to ORTHANC server
UI at http://localhost:8042
Add to your client configuration (e.g. claude_desktop_config.json
):
{
"mcpServers": {
"dicom": {
"command": "uv",
"args": ["tool","dicom-mcp", "/path/to/your_config.yaml"]
}
}
}
For development:
{
"mcpServers": {
"arxiv-mcp-server": {
"command": "uv",
"args": [
"--directory",
"path/to/cloned/dicom-mcp",
"run",
"dicom-mcp",
"/path/to/your_config.yaml"
]
}
}
}
dicom-mcp
provides four categories of tools for interaction with DICOM servers and DICOM data.
query_patients
: Search for patients based on criteria like name, ID, or birth date.query_studies
: Find studies using patient ID, date, modality, description, accession number, or Study UID.query_series
: Locate series within a specific study using modality, series number/description, or Series UID.query_instances
: Find individual instances (images/objects) within a series using instance number or SOP Instance UID
extract_pdf_text_from_dicom
: Retrieve a specific DICOM instance containing an encapsulated PDF and extract its text content.
move_series
: Send a specific DICOM series to another configured DICOM node using C-MOVE.move_study
: Send an entire DICOM study to another configured DICOM node using C-MOVE.
list_dicom_nodes
: Show the currently active DICOM node and list all configured nodes.switch_dicom_node
: Change the active DICOM node for subsequent operations.verify_connection
: Test the DICOM network connection to the currently active node using C-ECHO.get_attribute_presets
: List the available levels of detail (minimal, standard, extended) for metadata query results.
The tools can be chained together to answer complex questions:
Tests require a running Orthanc DICOM server. You can use Docker:
# Navigate to the directory containing docker-compose.yml (e.g., tests/)
cd tests
docker-compose up -d
Run tests using pytest:
# From the project root directory
pytest
Stop the Orthanc container:
cd tests
docker-compose down
Use the MCP Inspector for debugging the server communication:
npx @modelcontextprotocol/inspector uv run dicom-mcp /path/to/your_config.yaml --transport stdio
- Built using pynetdicom
- Uses PyPDF2 for PDF text extraction